End of training
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README.md
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---
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library_name: peft
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base_model: NousResearch/CodeLlama-13b-hf
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tags:
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- axolotl
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- generated_from_trainer
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model-index:
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- name: dd3b743e-a297-4b82-91c0-d205d2c68439
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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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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<br>
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# dd3b743e-a297-4b82-91c0-d205d2c68439
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This model is a fine-tuned version of [NousResearch/CodeLlama-13b-hf](https://huggingface.co/NousResearch/CodeLlama-13b-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4035
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.000213
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 50
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- training_steps: 500
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| No log | 0.0002 | 1 | 2.3596 |
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| 2.5945 | 0.0120 | 50 | 0.7943 |
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| 2.4573 | 0.0240 | 100 | 0.6662 |
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| 1.8716 | 0.0360 | 150 | 0.6166 |
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| 1.6216 | 0.0480 | 200 | 0.5558 |
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| 1.425 | 0.0600 | 250 | 0.5099 |
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| 1.4697 | 0.0720 | 300 | 0.4768 |
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| 1.4215 | 0.0839 | 350 | 0.4427 |
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| 1.8168 | 0.0959 | 400 | 0.4213 |
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| 1.2723 | 0.1079 | 450 | 0.4078 |
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| 1.0251 | 0.1199 | 500 | 0.4035 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.46.0
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- Pytorch 2.5.0+cu124
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- Datasets 3.0.1
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- Tokenizers 0.20.1
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