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--- |
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license: llama2 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: codellama/CodeLlama-13b-hf |
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model-index: |
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- name: lora-out |
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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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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# lora-out |
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This model is a fine-tuned version of [codellama/CodeLlama-13b-hf](https://huggingface.co./codellama/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: 0.4263 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.7628 | 0.01 | 1 | 0.7296 | |
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| 0.7101 | 0.05 | 7 | 0.6906 | |
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| 0.5395 | 0.1 | 14 | 0.5214 | |
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| 0.5303 | 0.15 | 21 | 0.4871 | |
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| 0.4821 | 0.2 | 28 | 0.4676 | |
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| 0.5643 | 0.25 | 35 | 0.4563 | |
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| 0.5307 | 0.3 | 42 | 0.4484 | |
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| 0.5103 | 0.35 | 49 | 0.4445 | |
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| 0.5515 | 0.4 | 56 | 0.4415 | |
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| 0.4983 | 0.45 | 63 | 0.4386 | |
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| 0.4919 | 0.5 | 70 | 0.4351 | |
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| 0.4674 | 0.55 | 77 | 0.4316 | |
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| 0.5193 | 0.6 | 84 | 0.4295 | |
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| 0.4461 | 0.65 | 91 | 0.4295 | |
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| 0.4541 | 0.71 | 98 | 0.4280 | |
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| 0.486 | 0.76 | 105 | 0.4280 | |
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| 0.4875 | 0.81 | 112 | 0.4269 | |
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| 0.5553 | 0.86 | 119 | 0.4266 | |
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| 0.4605 | 0.91 | 126 | 0.4260 | |
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| 0.4767 | 0.96 | 133 | 0.4263 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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## Training procedure |
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### Framework versions |
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- PEFT 0.6.0 |
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