Upload folder using huggingface_hub

README.md

@@ -1,3 +1,78 @@
----
-license: mit
----
+---
+library_name: peft
+license: other
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+tags:
+- llama-factory
+- lora
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: factory_mistral_results
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# factory_mistral_results
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the train dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2338
+- Accuracy: 0.9602
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 3
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 24
+- total_eval_batch_size: 6
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 9.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.3408        | 1.0    | 42   | 0.2954          | 0.9288   |
+| 0.1923        | 2.0    | 84   | 0.2233          | 0.9454   |
+| 0.1369        | 3.0    | 126  | 0.1945          | 0.9522   |
+| 0.1333        | 4.0    | 168  | 0.1867          | 0.9564   |
+| 0.0738        | 5.0    | 210  | 0.1909          | 0.9573   |
+| 0.0549        | 6.0    | 252  | 0.2025          | 0.9595   |
+| 0.0246        | 7.0    | 294  | 0.2197          | 0.9601   |
+| 0.0216        | 8.0    | 336  | 0.2324          | 0.9601   |
+| 0.0131        | 8.7904 | 369  | 0.2338          | 0.9602   |
+
+
+### Framework versions
+
+- PEFT 0.15.2
+- Transformers 4.51.3
+- Pytorch 2.7.1+cu126
+- Datasets 3.6.0
+- Tokenizers 0.21.1

adapter_config.json

@@ -0,0 +1,39 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "down_proj",
+    "v_proj",
+    "gate_proj",
+    "o_proj",
+    "k_proj",
+    "up_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:258e40ef65409d838f1d7c3aa128c7e065fb5d7c444f81cab3006e7bfb0f988d
+size 335604696

all_results.json

@@ -0,0 +1,13 @@
+{
+    "epoch": 8.790419161676647,
+    "eval_accuracy": 0.9601709260426984,
+    "eval_loss": 0.23376664519309998,
+    "eval_runtime": 29.1377,
+    "eval_samples_per_second": 13.213,
+    "eval_steps_per_second": 2.231,
+    "total_flos": 3.347106394674299e+17,
+    "train_loss": 0.14184355957882838,
+    "train_runtime": 2687.5102,
+    "train_samples_per_second": 3.349,
+    "train_steps_per_second": 0.137
+}

checkpoint-369/README.md

@@ -0,0 +1,202 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.15.2

checkpoint-369/adapter_config.json

@@ -0,0 +1,39 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "down_proj",
+    "v_proj",
+    "gate_proj",
+    "o_proj",
+    "k_proj",
+    "up_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

checkpoint-369/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:258e40ef65409d838f1d7c3aa128c7e065fb5d7c444f81cab3006e7bfb0f988d
+size 335604696

checkpoint-369/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5a27ac670074854f51a5861c9e1fd20c930e48f1e16f2fe3976b320550dcaa4d
+size 671467171

checkpoint-369/rng_state_0.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:93b75580b0ea18fc4ce71947f49b91150e4a81e1650cdbdf7625831bd9286bab
+size 15173

checkpoint-369/rng_state_1.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7ce05d2496f323b227fedf4553965913b0157f69d29cf63b3402ed21e49850df
+size 15173

checkpoint-369/rng_state_2.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0fa215a2c2b8d91e69b9adc06b04d1e0495e79b8c4087ef901482a6cc0b131ae
+size 15173

checkpoint-369/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:424755b5494adc5c2f757e98ba4ae1e8a1e2f36783c0fc67336778e50397db71
+size 1465

checkpoint-369/special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

checkpoint-369/tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
+size 587404

checkpoint-369/trainer_state.json

@@ -0,0 +1,358 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 8.790419161676647,
+  "eval_steps": 500,
+  "global_step": 369,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.23952095808383234,
+      "grad_norm": 1.0734883546829224,
+      "learning_rate": 7.500000000000001e-05,
+      "loss": 1.0376,
+      "step": 10
+    },
+    {
+      "epoch": 0.47904191616766467,
+      "grad_norm": 0.5477334856987,
+      "learning_rate": 9.990516643685222e-05,
+      "loss": 0.5249,
+      "step": 20
+    },
+    {
+      "epoch": 0.718562874251497,
+      "grad_norm": 0.5087978839874268,
+      "learning_rate": 9.944154131125642e-05,
+      "loss": 0.3878,
+      "step": 30
+    },
+    {
+      "epoch": 0.9580838323353293,
+      "grad_norm": 0.4627484977245331,
+      "learning_rate": 9.859528969650738e-05,
+      "loss": 0.3408,
+      "step": 40
+    },
+    {
+      "epoch": 1.0,
+      "eval_accuracy": 0.9287885233004581,
+      "eval_loss": 0.29543060064315796,
+      "eval_runtime": 29.2437,
+      "eval_samples_per_second": 13.165,
+      "eval_steps_per_second": 2.223,
+      "step": 42
+    },
+    {
+      "epoch": 1.1916167664670658,
+      "grad_norm": 0.4231412708759308,
+      "learning_rate": 9.737296070648186e-05,
+      "loss": 0.2531,
+      "step": 50
+    },
+    {
+      "epoch": 1.4311377245508983,
+      "grad_norm": 0.5066399574279785,
+      "learning_rate": 9.57840139057007e-05,
+      "loss": 0.2522,
+      "step": 60
+    },
+    {
+      "epoch": 1.6706586826347305,
+      "grad_norm": 0.5796340703964233,
+      "learning_rate": 9.384074610206495e-05,
+      "loss": 0.2588,
+      "step": 70
+    },
+    {
+      "epoch": 1.910179640718563,
+      "grad_norm": 0.431496262550354,
+      "learning_rate": 9.155819618225708e-05,
+      "loss": 0.1923,
+      "step": 80
+    },
+    {
+      "epoch": 2.0,
+      "eval_accuracy": 0.9453862057863471,
+      "eval_loss": 0.22325021028518677,
+      "eval_runtime": 29.1713,
+      "eval_samples_per_second": 13.198,
+      "eval_steps_per_second": 2.228,
+      "step": 84
+    },
+    {
+      "epoch": 2.143712574850299,
+      "grad_norm": 0.3872606158256531,
+      "learning_rate": 8.895402872628352e-05,
+      "loss": 0.2022,
+      "step": 90
+    },
+    {
+      "epoch": 2.3832335329341316,
+      "grad_norm": 0.5072871446609497,
+      "learning_rate": 8.604839730186125e-05,
+      "loss": 0.1489,
+      "step": 100
+    },
+    {
+      "epoch": 2.622754491017964,
+      "grad_norm": 0.5924299955368042,
+      "learning_rate": 8.286378849660896e-05,
+      "loss": 0.1807,
+      "step": 110
+    },
+    {
+      "epoch": 2.8622754491017965,
+      "grad_norm": 0.5023337602615356,
+      "learning_rate": 7.942484789507283e-05,
+      "loss": 0.1369,
+      "step": 120
+    },
+    {
+      "epoch": 3.0,
+      "eval_accuracy": 0.9521505982560647,
+      "eval_loss": 0.19450804591178894,
+      "eval_runtime": 29.0414,
+      "eval_samples_per_second": 13.257,
+      "eval_steps_per_second": 2.238,
+      "step": 126
+    },
+    {
+      "epoch": 3.095808383233533,
+      "grad_norm": 0.4512905180454254,
+      "learning_rate": 7.57581893473448e-05,
+      "loss": 0.1228,
+      "step": 130
+    },
+    {
+      "epoch": 3.3353293413173652,
+      "grad_norm": 0.43206489086151123,
+      "learning_rate": 7.18921890053375e-05,
+      "loss": 0.0949,
+      "step": 140
+    },
+    {
+      "epoch": 3.5748502994011977,
+      "grad_norm": 0.43717867136001587,
+      "learning_rate": 6.785676572066225e-05,
+      "loss": 0.1072,
+      "step": 150
+    },
+    {
+      "epoch": 3.81437125748503,
+      "grad_norm": 0.5549845695495605,
+      "learning_rate": 6.368314950360415e-05,
+      "loss": 0.1333,
+      "step": 160
+    },
+    {
+      "epoch": 4.0,
+      "eval_accuracy": 0.9563760579587307,
+      "eval_loss": 0.18670041859149933,
+      "eval_runtime": 29.043,
+      "eval_samples_per_second": 13.256,
+      "eval_steps_per_second": 2.238,
+      "step": 168
+    },
+    {
+      "epoch": 4.047904191616767,
+      "grad_norm": 0.3298746645450592,
+      "learning_rate": 5.940363983508257e-05,
+      "loss": 0.0838,
+      "step": 170
+    },
+    {
+      "epoch": 4.287425149700598,
+      "grad_norm": 0.5451555252075195,
+      "learning_rate": 5.5051355702012893e-05,
+      "loss": 0.0805,
+      "step": 180
+    },
+    {
+      "epoch": 4.526946107784431,
+      "grad_norm": 0.5960578322410583,
+      "learning_rate": 5.0659979290537954e-05,
+      "loss": 0.0664,
+      "step": 190
+    },
+    {
+      "epoch": 4.766467065868263,
+      "grad_norm": 0.5429267883300781,
+      "learning_rate": 4.626349532067879e-05,
+      "loss": 0.0628,
+      "step": 200
+    },
+    {
+      "epoch": 5.0,
+      "grad_norm": 0.43659478425979614,
+      "learning_rate": 4.189592803968563e-05,
+      "loss": 0.0738,
+      "step": 210
+    },
+    {
+      "epoch": 5.0,
+      "eval_accuracy": 0.9573371652464306,
+      "eval_loss": 0.19091445207595825,
+      "eval_runtime": 29.1306,
+      "eval_samples_per_second": 13.216,
+      "eval_steps_per_second": 2.231,
+      "step": 210
+    },
+    {
+      "epoch": 5.2395209580838324,
+      "grad_norm": 0.36590853333473206,
+      "learning_rate": 3.759107790948882e-05,
+      "loss": 0.046,
+      "step": 220
+    },
+    {
+      "epoch": 5.479041916167665,
+      "grad_norm": 0.4938795566558838,
+      "learning_rate": 3.338226002601703e-05,
+      "loss": 0.0464,
+      "step": 230
+    },
+    {
+      "epoch": 5.718562874251497,
+      "grad_norm": 0.41811272501945496,
+      "learning_rate": 2.9302046294747497e-05,
+      "loss": 0.0438,
+      "step": 240
+    },
+    {
+      "epoch": 5.95808383233533,
+      "grad_norm": 0.37814924120903015,
+      "learning_rate": 2.5382013357782893e-05,
+      "loss": 0.0549,
+      "step": 250
+    },
+    {
+      "epoch": 6.0,
+      "eval_accuracy": 0.9595451069080204,
+      "eval_loss": 0.2025168389081955,
+      "eval_runtime": 29.0421,
+      "eval_samples_per_second": 13.257,
+      "eval_steps_per_second": 2.238,
+      "step": 252
+    },
+    {
+      "epoch": 6.191616766467066,
+      "grad_norm": 0.4280014634132385,
+      "learning_rate": 2.1652498223239427e-05,
+      "loss": 0.038,
+      "step": 260
+    },
+    {
+      "epoch": 6.431137724550898,
+      "grad_norm": 0.367276132106781,
+      "learning_rate": 1.814236348812211e-05,
+      "loss": 0.0453,
+      "step": 270
+    },
+    {
+      "epoch": 6.6706586826347305,
+      "grad_norm": 0.6734885573387146,
+      "learning_rate": 1.4878773971620074e-05,
+      "loss": 0.0255,
+      "step": 280
+    },
+    {
+      "epoch": 6.910179640718563,
+      "grad_norm": 0.43918535113334656,
+      "learning_rate": 1.1886986487449475e-05,
+      "loss": 0.0246,
+      "step": 290
+    },
+    {
+      "epoch": 7.0,
+      "eval_accuracy": 0.9601195563525197,
+      "eval_loss": 0.2196582704782486,
+      "eval_runtime": 29.0921,
+      "eval_samples_per_second": 13.234,
+      "eval_steps_per_second": 2.234,
+      "step": 294
+    },
+    {
+      "epoch": 7.1437125748503,
+      "grad_norm": 0.2443029135465622,
+      "learning_rate": 9.190154382188921e-06,
+      "loss": 0.0188,
+      "step": 300
+    },
+    {
+      "epoch": 7.383233532934132,
+      "grad_norm": 0.2125871330499649,
+      "learning_rate": 6.809148352279182e-06,
+      "loss": 0.0199,
+      "step": 310
+    },
+    {
+      "epoch": 7.6227544910179645,
+      "grad_norm": 0.25036877393722534,
+      "learning_rate": 4.762394926378477e-06,
+      "loss": 0.0335,
+      "step": 320
+    },
+    {
+      "epoch": 7.862275449101796,
+      "grad_norm": 0.2146039605140686,
+      "learning_rate": 3.065733863053072e-06,
+      "loss": 0.0216,
+      "step": 330
+    },
+    {
+      "epoch": 8.0,
+      "eval_accuracy": 0.9601274555153836,
+      "eval_loss": 0.232394278049469,
+      "eval_runtime": 29.1106,
+      "eval_samples_per_second": 13.225,
+      "eval_steps_per_second": 2.233,
+      "step": 336
+    },
+    {
+      "epoch": 8.095808383233534,
+      "grad_norm": 0.20316274464130402,
+      "learning_rate": 1.7322955673980678e-06,
+      "loss": 0.0204,
+      "step": 340
+    },
+    {
+      "epoch": 8.335329341317365,
+      "grad_norm": 0.19030429422855377,
+      "learning_rate": 7.723994752570462e-07,
+      "loss": 0.0287,
+      "step": 350
+    },
+    {
+      "epoch": 8.574850299401197,
+      "grad_norm": 0.2464722841978073,
+      "learning_rate": 1.9347419144180035e-07,
+      "loss": 0.0131,
+      "step": 360
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 369,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 3.347106394674299e+17,
+  "train_batch_size": 2,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-369/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6625c94ac81d774713d80906f0c3c17652ae34d6cb07d755ad005e3fe18320f
+size 6097

eval_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 8.790419161676647,
+    "eval_accuracy": 0.9601709260426984,
+    "eval_loss": 0.23376664519309998,
+    "eval_runtime": 29.1377,
+    "eval_samples_per_second": 13.213,
+    "eval_steps_per_second": 2.231
+}

runs/Jul31_20-21-32_pan/events.out.tfevents.1754007813.pan

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb42f9c853ac245f3ec8ad592236cb423b7d17e20c24d8a343344b96a59fa5b3
+size 16092

runs/Jul31_20-21-32_pan/events.out.tfevents.1754010528.pan

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7b1196415c789c924902a2e1669439b3d21d1ccab1cce970b4321610937a558e
+size 363

special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
+size 587404

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 8.790419161676647,
+    "total_flos": 3.347106394674299e+17,
+    "train_loss": 0.14184355957882838,
+    "train_runtime": 2687.5102,
+    "train_samples_per_second": 3.349,
+    "train_steps_per_second": 0.137
+}

trainer_log.jsonl

@@ -0,0 +1,46 @@
+{"current_steps": 10, "total_steps": 369, "loss": 1.0376, "lr": 7.500000000000001e-05, "epoch": 0.23952095808383234, "percentage": 2.71, "elapsed_time": "0:01:04", "remaining_time": "0:38:46"}
+{"current_steps": 20, "total_steps": 369, "loss": 0.5249, "lr": 9.990516643685222e-05, "epoch": 0.47904191616766467, "percentage": 5.42, "elapsed_time": "0:02:09", "remaining_time": "0:37:31"}
+{"current_steps": 30, "total_steps": 369, "loss": 0.3878, "lr": 9.944154131125642e-05, "epoch": 0.718562874251497, "percentage": 8.13, "elapsed_time": "0:03:14", "remaining_time": "0:36:39"}
+{"current_steps": 40, "total_steps": 369, "loss": 0.3408, "lr": 9.859528969650738e-05, "epoch": 0.9580838323353293, "percentage": 10.84, "elapsed_time": "0:04:21", "remaining_time": "0:35:50"}
+{"current_steps": 42, "total_steps": 369, "eval_loss": 0.29543060064315796, "epoch": 1.0, "percentage": 11.38, "elapsed_time": "0:05:02", "remaining_time": "0:39:17"}
+{"current_steps": 50, "total_steps": 369, "loss": 0.2531, "lr": 9.737296070648186e-05, "epoch": 1.1916167664670658, "percentage": 13.55, "elapsed_time": "0:05:57", "remaining_time": "0:38:00"}
+{"current_steps": 60, "total_steps": 369, "loss": 0.2522, "lr": 9.57840139057007e-05, "epoch": 1.4311377245508983, "percentage": 16.26, "elapsed_time": "0:07:03", "remaining_time": "0:36:18"}
+{"current_steps": 70, "total_steps": 369, "loss": 0.2588, "lr": 9.384074610206495e-05, "epoch": 1.6706586826347305, "percentage": 18.97, "elapsed_time": "0:08:08", "remaining_time": "0:34:48"}
+{"current_steps": 80, "total_steps": 369, "loss": 0.1923, "lr": 9.155819618225708e-05, "epoch": 1.910179640718563, "percentage": 21.68, "elapsed_time": "0:09:15", "remaining_time": "0:33:26"}
+{"current_steps": 84, "total_steps": 369, "eval_loss": 0.22325021028518677, "epoch": 2.0, "percentage": 22.76, "elapsed_time": "0:10:08", "remaining_time": "0:34:25"}
+{"current_steps": 90, "total_steps": 369, "loss": 0.2022, "lr": 8.895402872628352e-05, "epoch": 2.143712574850299, "percentage": 24.39, "elapsed_time": "0:10:49", "remaining_time": "0:33:32"}
+{"current_steps": 100, "total_steps": 369, "loss": 0.1489, "lr": 8.604839730186125e-05, "epoch": 2.3832335329341316, "percentage": 27.1, "elapsed_time": "0:11:55", "remaining_time": "0:32:04"}
+{"current_steps": 110, "total_steps": 369, "loss": 0.1807, "lr": 8.286378849660896e-05, "epoch": 2.622754491017964, "percentage": 29.81, "elapsed_time": "0:13:01", "remaining_time": "0:30:39"}
+{"current_steps": 120, "total_steps": 369, "loss": 0.1369, "lr": 7.942484789507283e-05, "epoch": 2.8622754491017965, "percentage": 32.52, "elapsed_time": "0:14:07", "remaining_time": "0:29:17"}
+{"current_steps": 126, "total_steps": 369, "eval_loss": 0.19450804591178894, "epoch": 3.0, "percentage": 34.15, "elapsed_time": "0:15:13", "remaining_time": "0:29:22"}
+{"current_steps": 130, "total_steps": 369, "loss": 0.1228, "lr": 7.57581893473448e-05, "epoch": 3.095808383233533, "percentage": 35.23, "elapsed_time": "0:15:40", "remaining_time": "0:28:48"}
+{"current_steps": 140, "total_steps": 369, "loss": 0.0949, "lr": 7.18921890053375e-05, "epoch": 3.3353293413173652, "percentage": 37.94, "elapsed_time": "0:16:45", "remaining_time": "0:27:25"}
+{"current_steps": 150, "total_steps": 369, "loss": 0.1072, "lr": 6.785676572066225e-05, "epoch": 3.5748502994011977, "percentage": 40.65, "elapsed_time": "0:17:52", "remaining_time": "0:26:05"}
+{"current_steps": 160, "total_steps": 369, "loss": 0.1333, "lr": 6.368314950360415e-05, "epoch": 3.81437125748503, "percentage": 43.36, "elapsed_time": "0:18:57", "remaining_time": "0:24:45"}
+{"current_steps": 168, "total_steps": 369, "eval_loss": 0.18670041859149933, "epoch": 4.0, "percentage": 45.53, "elapsed_time": "0:20:18", "remaining_time": "0:24:17"}
+{"current_steps": 170, "total_steps": 369, "loss": 0.0838, "lr": 5.940363983508257e-05, "epoch": 4.047904191616767, "percentage": 46.07, "elapsed_time": "0:20:31", "remaining_time": "0:24:01"}
+{"current_steps": 180, "total_steps": 369, "loss": 0.0805, "lr": 5.5051355702012893e-05, "epoch": 4.287425149700598, "percentage": 48.78, "elapsed_time": "0:21:38", "remaining_time": "0:22:43"}
+{"current_steps": 190, "total_steps": 369, "loss": 0.0664, "lr": 5.0659979290537954e-05, "epoch": 4.526946107784431, "percentage": 51.49, "elapsed_time": "0:22:43", "remaining_time": "0:21:24"}
+{"current_steps": 200, "total_steps": 369, "loss": 0.0628, "lr": 4.626349532067879e-05, "epoch": 4.766467065868263, "percentage": 54.2, "elapsed_time": "0:23:49", "remaining_time": "0:20:07"}
+{"current_steps": 210, "total_steps": 369, "loss": 0.0738, "lr": 4.189592803968563e-05, "epoch": 5.0, "percentage": 56.91, "elapsed_time": "0:24:52", "remaining_time": "0:18:50"}
+{"current_steps": 210, "total_steps": 369, "eval_loss": 0.19091445207595825, "epoch": 5.0, "percentage": 56.91, "elapsed_time": "0:25:22", "remaining_time": "0:19:12"}
+{"current_steps": 220, "total_steps": 369, "loss": 0.046, "lr": 3.759107790948882e-05, "epoch": 5.2395209580838324, "percentage": 59.62, "elapsed_time": "0:26:28", "remaining_time": "0:17:55"}
+{"current_steps": 230, "total_steps": 369, "loss": 0.0464, "lr": 3.338226002601703e-05, "epoch": 5.479041916167665, "percentage": 62.33, "elapsed_time": "0:27:34", "remaining_time": "0:16:39"}
+{"current_steps": 240, "total_steps": 369, "loss": 0.0438, "lr": 2.9302046294747497e-05, "epoch": 5.718562874251497, "percentage": 65.04, "elapsed_time": "0:28:38", "remaining_time": "0:15:23"}
+{"current_steps": 250, "total_steps": 369, "loss": 0.0549, "lr": 2.5382013357782893e-05, "epoch": 5.95808383233533, "percentage": 67.75, "elapsed_time": "0:29:44", "remaining_time": "0:14:09"}
+{"current_steps": 252, "total_steps": 369, "eval_loss": 0.2025168389081955, "epoch": 6.0, "percentage": 68.29, "elapsed_time": "0:30:25", "remaining_time": "0:14:07"}
+{"current_steps": 260, "total_steps": 369, "loss": 0.038, "lr": 2.1652498223239427e-05, "epoch": 6.191616766467066, "percentage": 70.46, "elapsed_time": "0:31:18", "remaining_time": "0:13:07"}
+{"current_steps": 270, "total_steps": 369, "loss": 0.0453, "lr": 1.814236348812211e-05, "epoch": 6.431137724550898, "percentage": 73.17, "elapsed_time": "0:32:26", "remaining_time": "0:11:53"}
+{"current_steps": 280, "total_steps": 369, "loss": 0.0255, "lr": 1.4878773971620074e-05, "epoch": 6.6706586826347305, "percentage": 75.88, "elapsed_time": "0:33:30", "remaining_time": "0:10:39"}
+{"current_steps": 290, "total_steps": 369, "loss": 0.0246, "lr": 1.1886986487449475e-05, "epoch": 6.910179640718563, "percentage": 78.59, "elapsed_time": "0:34:35", "remaining_time": "0:09:25"}
+{"current_steps": 294, "total_steps": 369, "eval_loss": 0.2196582704782486, "epoch": 7.0, "percentage": 79.67, "elapsed_time": "0:35:29", "remaining_time": "0:09:03"}
+{"current_steps": 300, "total_steps": 369, "loss": 0.0188, "lr": 9.190154382188921e-06, "epoch": 7.1437125748503, "percentage": 81.3, "elapsed_time": "0:36:10", "remaining_time": "0:08:19"}
+{"current_steps": 310, "total_steps": 369, "loss": 0.0199, "lr": 6.809148352279182e-06, "epoch": 7.383233532934132, "percentage": 84.01, "elapsed_time": "0:37:16", "remaining_time": "0:07:05"}
+{"current_steps": 320, "total_steps": 369, "loss": 0.0335, "lr": 4.762394926378477e-06, "epoch": 7.6227544910179645, "percentage": 86.72, "elapsed_time": "0:38:22", "remaining_time": "0:05:52"}
+{"current_steps": 330, "total_steps": 369, "loss": 0.0216, "lr": 3.065733863053072e-06, "epoch": 7.862275449101796, "percentage": 89.43, "elapsed_time": "0:39:28", "remaining_time": "0:04:39"}
+{"current_steps": 336, "total_steps": 369, "eval_loss": 0.232394278049469, "epoch": 8.0, "percentage": 91.06, "elapsed_time": "0:40:36", "remaining_time": "0:03:59"}
+{"current_steps": 340, "total_steps": 369, "loss": 0.0204, "lr": 1.7322955673980678e-06, "epoch": 8.095808383233534, "percentage": 92.14, "elapsed_time": "0:41:02", "remaining_time": "0:03:30"}
+{"current_steps": 350, "total_steps": 369, "loss": 0.0287, "lr": 7.723994752570462e-07, "epoch": 8.335329341317365, "percentage": 94.85, "elapsed_time": "0:42:08", "remaining_time": "0:02:17"}
+{"current_steps": 360, "total_steps": 369, "loss": 0.0131, "lr": 1.9347419144180035e-07, "epoch": 8.574850299401197, "percentage": 97.56, "elapsed_time": "0:43:13", "remaining_time": "0:01:04"}
+{"current_steps": 369, "total_steps": 369, "eval_loss": 0.23376664519309998, "epoch": 8.790419161676647, "percentage": 100.0, "elapsed_time": "0:44:44", "remaining_time": "0:00:00"}
+{"current_steps": 369, "total_steps": 369, "epoch": 8.790419161676647, "percentage": 100.0, "elapsed_time": "0:44:44", "remaining_time": "0:00:00"}

trainer_state.json

@@ -0,0 +1,376 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 8.790419161676647,
+  "eval_steps": 500,
+  "global_step": 369,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.23952095808383234,
+      "grad_norm": 1.0734883546829224,
+      "learning_rate": 7.500000000000001e-05,
+      "loss": 1.0376,
+      "step": 10
+    },
+    {
+      "epoch": 0.47904191616766467,
+      "grad_norm": 0.5477334856987,
+      "learning_rate": 9.990516643685222e-05,
+      "loss": 0.5249,
+      "step": 20
+    },
+    {
+      "epoch": 0.718562874251497,
+      "grad_norm": 0.5087978839874268,
+      "learning_rate": 9.944154131125642e-05,
+      "loss": 0.3878,
+      "step": 30
+    },
+    {
+      "epoch": 0.9580838323353293,
+      "grad_norm": 0.4627484977245331,
+      "learning_rate": 9.859528969650738e-05,
+      "loss": 0.3408,
+      "step": 40
+    },
+    {
+      "epoch": 1.0,
+      "eval_accuracy": 0.9287885233004581,
+      "eval_loss": 0.29543060064315796,
+      "eval_runtime": 29.2437,
+      "eval_samples_per_second": 13.165,
+      "eval_steps_per_second": 2.223,
+      "step": 42
+    },
+    {
+      "epoch": 1.1916167664670658,
+      "grad_norm": 0.4231412708759308,
+      "learning_rate": 9.737296070648186e-05,
+      "loss": 0.2531,
+      "step": 50
+    },
+    {
+      "epoch": 1.4311377245508983,
+      "grad_norm": 0.5066399574279785,
+      "learning_rate": 9.57840139057007e-05,
+      "loss": 0.2522,
+      "step": 60
+    },
+    {
+      "epoch": 1.6706586826347305,
+      "grad_norm": 0.5796340703964233,
+      "learning_rate": 9.384074610206495e-05,
+      "loss": 0.2588,
+      "step": 70
+    },
+    {
+      "epoch": 1.910179640718563,
+      "grad_norm": 0.431496262550354,
+      "learning_rate": 9.155819618225708e-05,
+      "loss": 0.1923,
+      "step": 80
+    },
+    {
+      "epoch": 2.0,
+      "eval_accuracy": 0.9453862057863471,
+      "eval_loss": 0.22325021028518677,
+      "eval_runtime": 29.1713,
+      "eval_samples_per_second": 13.198,
+      "eval_steps_per_second": 2.228,
+      "step": 84
+    },
+    {
+      "epoch": 2.143712574850299,
+      "grad_norm": 0.3872606158256531,
+      "learning_rate": 8.895402872628352e-05,
+      "loss": 0.2022,
+      "step": 90
+    },
+    {
+      "epoch": 2.3832335329341316,
+      "grad_norm": 0.5072871446609497,
+      "learning_rate": 8.604839730186125e-05,
+      "loss": 0.1489,
+      "step": 100
+    },
+    {
+      "epoch": 2.622754491017964,
+      "grad_norm": 0.5924299955368042,
+      "learning_rate": 8.286378849660896e-05,
+      "loss": 0.1807,
+      "step": 110
+    },
+    {
+      "epoch": 2.8622754491017965,
+      "grad_norm": 0.5023337602615356,
+      "learning_rate": 7.942484789507283e-05,
+      "loss": 0.1369,
+      "step": 120
+    },
+    {
+      "epoch": 3.0,
+      "eval_accuracy": 0.9521505982560647,
+      "eval_loss": 0.19450804591178894,
+      "eval_runtime": 29.0414,
+      "eval_samples_per_second": 13.257,
+      "eval_steps_per_second": 2.238,
+      "step": 126
+    },
+    {
+      "epoch": 3.095808383233533,
+      "grad_norm": 0.4512905180454254,
+      "learning_rate": 7.57581893473448e-05,
+      "loss": 0.1228,
+      "step": 130
+    },
+    {
+      "epoch": 3.3353293413173652,
+      "grad_norm": 0.43206489086151123,
+      "learning_rate": 7.18921890053375e-05,
+      "loss": 0.0949,
+      "step": 140
+    },
+    {
+      "epoch": 3.5748502994011977,
+      "grad_norm": 0.43717867136001587,
+      "learning_rate": 6.785676572066225e-05,
+      "loss": 0.1072,
+      "step": 150
+    },
+    {
+      "epoch": 3.81437125748503,
+      "grad_norm": 0.5549845695495605,
+      "learning_rate": 6.368314950360415e-05,
+      "loss": 0.1333,
+      "step": 160
+    },
+    {
+      "epoch": 4.0,
+      "eval_accuracy": 0.9563760579587307,
+      "eval_loss": 0.18670041859149933,
+      "eval_runtime": 29.043,
+      "eval_samples_per_second": 13.256,
+      "eval_steps_per_second": 2.238,
+      "step": 168
+    },
+    {
+      "epoch": 4.047904191616767,
+      "grad_norm": 0.3298746645450592,
+      "learning_rate": 5.940363983508257e-05,
+      "loss": 0.0838,
+      "step": 170
+    },
+    {
+      "epoch": 4.287425149700598,
+      "grad_norm": 0.5451555252075195,
+      "learning_rate": 5.5051355702012893e-05,
+      "loss": 0.0805,
+      "step": 180
+    },
+    {
+      "epoch": 4.526946107784431,
+      "grad_norm": 0.5960578322410583,
+      "learning_rate": 5.0659979290537954e-05,
+      "loss": 0.0664,
+      "step": 190
+    },
+    {
+      "epoch": 4.766467065868263,
+      "grad_norm": 0.5429267883300781,
+      "learning_rate": 4.626349532067879e-05,
+      "loss": 0.0628,
+      "step": 200
+    },
+    {
+      "epoch": 5.0,
+      "grad_norm": 0.43659478425979614,
+      "learning_rate": 4.189592803968563e-05,
+      "loss": 0.0738,
+      "step": 210
+    },
+    {
+      "epoch": 5.0,
+      "eval_accuracy": 0.9573371652464306,
+      "eval_loss": 0.19091445207595825,
+      "eval_runtime": 29.1306,
+      "eval_samples_per_second": 13.216,
+      "eval_steps_per_second": 2.231,
+      "step": 210
+    },
+    {
+      "epoch": 5.2395209580838324,
+      "grad_norm": 0.36590853333473206,
+      "learning_rate": 3.759107790948882e-05,
+      "loss": 0.046,
+      "step": 220
+    },
+    {
+      "epoch": 5.479041916167665,
+      "grad_norm": 0.4938795566558838,
+      "learning_rate": 3.338226002601703e-05,
+      "loss": 0.0464,
+      "step": 230
+    },
+    {
+      "epoch": 5.718562874251497,
+      "grad_norm": 0.41811272501945496,
+      "learning_rate": 2.9302046294747497e-05,
+      "loss": 0.0438,
+      "step": 240
+    },
+    {
+      "epoch": 5.95808383233533,
+      "grad_norm": 0.37814924120903015,
+      "learning_rate": 2.5382013357782893e-05,
+      "loss": 0.0549,
+      "step": 250
+    },
+    {
+      "epoch": 6.0,
+      "eval_accuracy": 0.9595451069080204,
+      "eval_loss": 0.2025168389081955,
+      "eval_runtime": 29.0421,
+      "eval_samples_per_second": 13.257,
+      "eval_steps_per_second": 2.238,
+      "step": 252
+    },
+    {
+      "epoch": 6.191616766467066,
+      "grad_norm": 0.4280014634132385,
+      "learning_rate": 2.1652498223239427e-05,
+      "loss": 0.038,
+      "step": 260
+    },
+    {
+      "epoch": 6.431137724550898,
+      "grad_norm": 0.367276132106781,
+      "learning_rate": 1.814236348812211e-05,
+      "loss": 0.0453,
+      "step": 270
+    },
+    {
+      "epoch": 6.6706586826347305,
+      "grad_norm": 0.6734885573387146,
+      "learning_rate": 1.4878773971620074e-05,
+      "loss": 0.0255,
+      "step": 280
+    },
+    {
+      "epoch": 6.910179640718563,
+      "grad_norm": 0.43918535113334656,
+      "learning_rate": 1.1886986487449475e-05,
+      "loss": 0.0246,
+      "step": 290
+    },
+    {
+      "epoch": 7.0,
+      "eval_accuracy": 0.9601195563525197,
+      "eval_loss": 0.2196582704782486,
+      "eval_runtime": 29.0921,
+      "eval_samples_per_second": 13.234,
+      "eval_steps_per_second": 2.234,
+      "step": 294
+    },
+    {
+      "epoch": 7.1437125748503,
+      "grad_norm": 0.2443029135465622,
+      "learning_rate": 9.190154382188921e-06,
+      "loss": 0.0188,
+      "step": 300
+    },
+    {
+      "epoch": 7.383233532934132,
+      "grad_norm": 0.2125871330499649,
+      "learning_rate": 6.809148352279182e-06,
+      "loss": 0.0199,
+      "step": 310
+    },
+    {
+      "epoch": 7.6227544910179645,
+      "grad_norm": 0.25036877393722534,
+      "learning_rate": 4.762394926378477e-06,
+      "loss": 0.0335,
+      "step": 320
+    },
+    {
+      "epoch": 7.862275449101796,
+      "grad_norm": 0.2146039605140686,
+      "learning_rate": 3.065733863053072e-06,
+      "loss": 0.0216,
+      "step": 330
+    },
+    {
+      "epoch": 8.0,
+      "eval_accuracy": 0.9601274555153836,
+      "eval_loss": 0.232394278049469,
+      "eval_runtime": 29.1106,
+      "eval_samples_per_second": 13.225,
+      "eval_steps_per_second": 2.233,
+      "step": 336
+    },
+    {
+      "epoch": 8.095808383233534,
+      "grad_norm": 0.20316274464130402,
+      "learning_rate": 1.7322955673980678e-06,
+      "loss": 0.0204,
+      "step": 340
+    },
+    {
+      "epoch": 8.335329341317365,
+      "grad_norm": 0.19030429422855377,
+      "learning_rate": 7.723994752570462e-07,
+      "loss": 0.0287,
+      "step": 350
+    },
+    {
+      "epoch": 8.574850299401197,
+      "grad_norm": 0.2464722841978073,
+      "learning_rate": 1.9347419144180035e-07,
+      "loss": 0.0131,
+      "step": 360
+    },
+    {
+      "epoch": 8.790419161676647,
+      "eval_accuracy": 0.9601709260426984,
+      "eval_loss": 0.23376664519309998,
+      "eval_runtime": 29.0302,
+      "eval_samples_per_second": 13.262,
+      "eval_steps_per_second": 2.239,
+      "step": 369
+    },
+    {
+      "epoch": 8.790419161676647,
+      "step": 369,
+      "total_flos": 3.347106394674299e+17,
+      "train_loss": 0.14184355957882838,
+      "train_runtime": 2687.5102,
+      "train_samples_per_second": 3.349,
+      "train_steps_per_second": 0.137
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 369,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 3.347106394674299e+17,
+  "train_batch_size": 2,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6625c94ac81d774713d80906f0c3c17652ae34d6cb07d755ad005e3fe18320f
+size 6097