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README.md

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+---
+license: bigcode-openrail-m
+library_name: peft
+tags:
+- generated_from_trainer
+datasets:
+- fals3/methods2test_small
+metrics:
+- accuracy
+base_model: bigcode/starcoderbase
+model-index:
+- name: output
+  results:
+  - task:
+      type: text-generation
+      name: Causal Language Modeling
+    dataset:
+      name: fals3/methods2test_small fm+fc+c+m+f+t+tc
+      type: fals3/methods2test_small
+      args: fm+fc+c+m+f+t+tc
+    metrics:
+    - type: accuracy
+      value: 0.720986037582824
+      name: Accuracy
+---
+
+<!-- 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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/fals3/methods2test_small/runs/e5c21kgm)
+# output
+
+This model is a fine-tuned version of [bigcode/starcoderbase](https://huggingface.co/bigcode/starcoderbase) on the fals3/methods2test_small fm+fc+c+m+f+t+tc dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6443
+- Accuracy: 0.7210
+
+## 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: 0.0003
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
+- total_eval_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0
+
+### Training results
+
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.41.0.dev0
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.1
+- Tokenizers 0.19.1

adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "bigcode/starcoderbase",
+  "fan_in_fan_out": false,
+  "feedforward_modules": [
+    "mlp.c_proj"
+  ],
+  "inference_mode": true,
+  "init_ia3_weights": true,
+  "modules_to_save": null,
+  "peft_type": "IA3",
+  "revision": null,
+  "target_modules": [
+    "mlp.c_proj",
+    "c_attn"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.bin

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+size 4967866

all_results.json

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+    "eval_accuracy": 0.720986037582824,
+    "eval_loss": 0.6443033814430237,
+    "eval_runtime": 73.8518,
+    "eval_samples": 931,
+    "eval_samples_per_second": 12.606,
+    "eval_steps_per_second": 6.31,
+    "perplexity": 1.904659745696835,
+    "total_flos": 1.0038997179244216e+18,
+    "train_loss": 0.6840552445296403,
+    "train_runtime": 5408.1966,
+    "train_samples": 7283,
+    "train_samples_per_second": 4.04,
+    "train_steps_per_second": 0.252
+}

eval_results.json

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+{
+    "epoch": 2.99835255354201,
+    "eval_accuracy": 0.720986037582824,
+    "eval_loss": 0.6443033814430237,
+    "eval_runtime": 73.8518,
+    "eval_samples": 931,
+    "eval_samples_per_second": 12.606,
+    "eval_steps_per_second": 6.31,
+    "perplexity": 1.904659745696835
+}

special_tokens_map.json

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tokenizer_config.json

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train_results.json

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