Duplicate from apriasmoro/de7fae79-1bd5-4ce4-b6fa-0e39b70b101f

Co-authored-by: Apriasmoro <[email protected]>

.gitattributes

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README.md

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+---
+library_name: peft
+tags:
+- axolotl
+- base_model:adapter:/cache/models/openai--gpt-oss-20b
+- lora
+- transformers
+pipeline_tag: text-generation
+base_model: openai/gpt-oss-20b
+model-index:
+- name: app/checkpoints/81d99e01-29b1-4f69-a23e-0dba6a297872/de7fae79-1bd5-4ce4-b6fa-0e39b70b101f
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.12.0`
+```yaml
+adapter: lora
+attn_implementation: eager
+base_model: openai/gpt-oss-20b
+bf16: true
+chat_template: llama3
+cosine_min_lr_ratio: 0.3
+dataloader_num_workers: 12
+dataset_prepared_path: null
+datasets:
+- data_files:
+  - 81d99e01-29b1-4f69-a23e-0dba6a297872_train_data.json
+  ds_type: json
+  format: custom
+  path: /workspace/axolotl/data
+  type:
+    field_instruction: instruct
+    field_output: output
+    format: '{instruction}'
+    no_input_format: '{instruction}'
+    system_format: '{system}'
+    system_prompt: ''
+ddp: true
+debug: null
+deepspeed: null
+device_map: cuda
+early_stopping_patience: null
+eval_max_new_tokens: 128
+eval_steps: null
+eval_table_size: null
+evals_per_epoch: null
+flash_attention: true
+fp16: false
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 1
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+group_by_length: true
+hub_model_id: null
+hub_private_repo: false
+hub_repo: null
+hub_strategy: checkpoint
+hub_token: null
+learning_rate: 0.0002
+liger_fused_linear_cross_entropy: true
+liger_glu_activation: true
+liger_layer_norm: true
+liger_rms_norm: true
+liger_rope: true
+load_in_4bit: false
+load_in_8bit: false
+local_rank: null
+logging_steps: null
+lora_alpha: 64
+lora_dropout: 0.05
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 32
+lora_target_linear: true
+loraplus_lr_embedding: 1.0e-06
+loraplus_lr_ratio: 16
+lr_scheduler: cosine
+max_grad_norm: 1
+max_steps: 4257
+micro_batch_size: 12
+mlflow_experiment_name: /workspace/axolotl/data/81d99e01-29b1-4f69-a23e-0dba6a297872_train_data.json
+model_card: false
+model_type: AutoModelForCausalLM
+num_epochs: 200
+optimizer: adamw_bnb_8bit
+output_dir: /app/checkpoints/81d99e01-29b1-4f69-a23e-0dba6a297872/de7fae79-1bd5-4ce4-b6fa-0e39b70b101f
+pad_to_sequence_len: true
+plugins:
+- axolotl.integrations.liger.LigerPlugin
+push_every_save: true
+push_to_hub: true
+resume_from_checkpoint: null
+rl: null
+s2_attention: null
+sample_packing: true
+save_steps: 100
+save_strategy: steps
+save_total_limit: 1
+saves_per_epoch: 0
+sequence_len: 512
+strict: false
+tf32: true
+tokenizer_type: AutoTokenizer
+train_on_inputs: false
+trl: null
+trust_remote_code: false
+use_flash_attention: false
+use_liger: true
+val_set_size: 0.0
+wandb_mode: offline
+wandb_name: 81d99e01-29b1-4f69-a23e-0dba6a297872_de7fae79-1bd5-4ce4-b6fa-0e39b70b101f
+wandb_project: Gradients-On-Demand
+wandb_run: null
+wandb_runid: 81d99e01-29b1-4f69-a23e-0dba6a297872_de7fae79-1bd5-4ce4-b6fa-0e39b70b101f
+warmup_steps: 200
+weight_decay: 0
+xformers_attention: null
+
+```
+
+</details><br>
+
+# app/checkpoints/81d99e01-29b1-4f69-a23e-0dba6a297872/de7fae79-1bd5-4ce4-b6fa-0e39b70b101f
+
+This model was trained from scratch on the None dataset.
+
+## 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: 0.0002
+- train_batch_size: 12
+- eval_batch_size: 12
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 200
+- training_steps: 4257
+
+### Training results
+
+
+
+### Framework versions
+
+- PEFT 0.17.0
+- Transformers 4.55.0
+- Pytorch 2.7.1+cu128
+- Datasets 4.0.0
+- Tokenizers 0.21.4

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "openai/gpt-oss-20b",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": null,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "q_proj",
+    "k_proj",
+    "o_proj"
+  ],
+  "target_parameters": [],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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chat_template.jinja

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+{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
+
+'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
+
+' }}{% endif %}

checkpoint-4257/README.md

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+---
+base_model: /cache/models/openai--gpt-oss-20b
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- axolotl
+- base_model:adapter:/cache/models/openai--gpt-oss-20b
+- lora
+- transformers
+---
+
+# 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 0.17.0

checkpoint-4257/adapter_config.json

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+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
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+  "target_modules": [
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