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--- |
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library_name: transformers |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- jondurbin/contextual-dpo-v0.1 |
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model-index: |
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- name: Tiny-Darkllama3.2-1B-Instruct-v0.2 |
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results: |
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- task: |
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type: arc_easy |
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dataset: |
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name: arc_easy |
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type: arc_easy |
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metrics: |
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- name: acc |
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type: accuracy |
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value: 0.2622 |
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stderr: 0.0090 |
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- name: acc_norm |
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type: normalized_accuracy |
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value: 0.2639 |
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stderr: 0.0090 |
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source: |
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name: eval-harness |
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url: https://github.com/EleutherAI/lm-evaluation-harness |
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base_model: unsloth/Llama-3.2-1B |
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--- |
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# Model Card for Tiny-Darkllama3.2-1B-Instruct-v0.2 |
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## Model Details |
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- **Model Name:** Tiny-Darkllama3.2-1B-Instruct-v0.2 |
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- **Base Model:** [unsloth/Llama-3.2-1B](https://huggingface.co/unsloth/Llama-3.2-1B) |
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- **Model Type:** LlamaForCausalLM |
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- **Training Framework:** Transformers 4.48.3 |
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- **Training Hardware:** NVIDIA GPU with CUDA 12.4 |
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## Training Data |
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- **Dataset:** [jondurbin/contextual-dpo-v0.1](https://huggingface.co/datasets/jondurbin/contextual-dpo-v0.1) |
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- **Training Split:** train |
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## Training Procedure |
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### Hyperparameters |
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- **Learning Rate:** 0.0002 |
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- **Optimizer:** AdamW |
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- **LR Scheduler:** Linear |
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- **Batch Size:** 1 |
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- **Gradient Accumulation Steps:** 1 |
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- **Max Steps:** 20 |
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- **Epochs:** 4 |
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- **Warmup Steps:** 10 |
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- **Weight Decay:** 0.0 |
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- **Sequence Length:** 1096 |
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### Training Configuration |
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- **Gradient Checkpointing:** Enabled |
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- **Sample Packing:** Enabled |
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- **Pad to Sequence Length:** True |
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- **Flash Attention:** Disabled |
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- **FP16/BF16:** Disabled |
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- **DeepSpeed/FSDP:** Not used |
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## Evaluation |
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### Results |
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- **ARC Easy Dataset:** |
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- Accuracy: 0.2622 |
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- Standard Error: 0.0090 |
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- Normalized Accuracy: 0.2639 |
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- Normalized Standard Error: 0.0090 |
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## Usage |
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This model is designed for instruction-following tasks and can be used for various natural language processing applications. It is fine-tuned using the DPO (Direct Preference Optimization) method on the contextual-dpo dataset. |
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## Limitations |
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- The model's performance may vary depending on the specific task and dataset. |
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- Fine-tuning on additional datasets may be required for optimal performance on specific tasks. |
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## Citation |
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If you use this model in your research, please cite the original Llama model and the Axolotl training framework. |
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## License |
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This model is licensed under the terms of the [License Name](link-to-license). |
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## Contact |
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For more information, please contact [Your Contact Information]. |
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[<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) |
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<details> |
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<summary>See Axolotl Config</summary> |
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```yaml |
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axolotl version: '0.6.0' |
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base_model: mrcuddle/tiny-darkllama3.2-1B |
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bf16: false |
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dataset_prepared_path: last_run_prepared |
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rl: dpo |
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datasets: |
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- path: jondurbin/contextual-dpo-v0.1 |
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field_messages: prompt |
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field_chosen: chosen |
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field_rejected: rejected |
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split: train |
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debug: null |
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deepspeed: null |
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early_stopping_patience: null |
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evals_per_epoch: null |
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flash_attention: false |
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fp16: false |
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fsdp: null |
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fsdp_config: null |
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gradient_accumulation_steps: 1 |
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gradient_checkpointing: true |
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group_by_length: false |
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hub_model_id: mrcuddle/Tiny-Darkllama3.2-1B-Instruct |
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is_llama_derived_model: true |
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learning_rate: 0.0002 |
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load_in_4bit: false |
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load_in_8bit: false |
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local_rank: null |
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logging_steps: 1 |
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lr_scheduler: linear |
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max_steps: 20 |
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micro_batch_size: 1 |
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mlflow_experiment_name: colab-example |
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model_type: LlamaForCausalLM |
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num_epochs: 4 |
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optimizer: adamw_torch |
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output_dir: ./llama2 |
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pad_to_sequence_len: true |
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resume_from_checkpoint: null |
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sample_packing: true |
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saves_per_epoch: null |
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sequence_len: 1096 |
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special_tokens: null |
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strict: false |
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tf32: false |
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tokenizer_type: LlamaTokenizer |
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train_on_inputs: false |
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wandb_entity: null |
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wandb_log_model: null |
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wandb_name: null |
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wandb_project: null |
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wandb_watch: null |
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warmup_steps: 10 |
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weight_decay: 0.0 |
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xformers_attention: null |
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``` |
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</details> |
