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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-7b-Instruct-hf |
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metrics: |
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- accuracy |
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- bleu |
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- sacrebleu |
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- rouge |
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model-index: |
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- name: CodeLlama-7b-Instruct-hf_Fi__CMP_TR_size_304_epochs_10_2024-06-22_21-11-23_3558625 |
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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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# CodeLlama-7b-Instruct-hf_Fi__CMP_TR_size_304_epochs_10_2024-06-22_21-11-23_3558625 |
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This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9442 |
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- Accuracy: 0.464 |
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- Chrf: 0.282 |
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- Bleu: 0.212 |
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- Sacrebleu: 0.2 |
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- Rouge1: 0.473 |
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- Rouge2: 0.304 |
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- Rougel: 0.447 |
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- Rougelsum: 0.467 |
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- Meteor: 0.474 |
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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: 0.001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 3407 |
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- distributed_type: multi-GPU |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 304 |
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- training_steps: 3040 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Chrf | Bleu | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----:|:---------:|:------:|:------:|:------:|:---------:|:------:| |
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| 0.7293 | 1.0 | 304 | 2.8400 | 0.471 | 0.109 | 0.089 | 0.1 | 0.318 | 0.168 | 0.304 | 0.297 | 0.274 | |
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| 0.043 | 2.0 | 608 | 3.2408 | 0.498 | 0.051 | 0.019 | 0.0 | 0.162 | 0.063 | 0.136 | 0.142 | 0.216 | |
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| 0.0514 | 3.0 | 912 | 2.8322 | 0.478 | 0.156 | 0.059 | 0.1 | 0.3 | 0.145 | 0.284 | 0.289 | 0.289 | |
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| 0.0145 | 4.0 | 1216 | 2.5898 | 0.478 | 0.101 | 0.064 | 0.1 | 0.263 | 0.167 | 0.258 | 0.258 | 0.32 | |
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| 0.8203 | 5.0 | 1520 | 2.7395 | 0.478 | 0.16 | 0.049 | 0.0 | 0.306 | 0.114 | 0.284 | 0.298 | 0.27 | |
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| 0.0546 | 6.0 | 1824 | 2.8379 | 0.458 | 0.052 | 0.022 | 0.0 | 0.068 | 0.0 | 0.056 | 0.057 | 0.21 | |
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| 0.0352 | 7.0 | 2128 | 2.6987 | 0.481 | 0.165 | 0.133 | 0.1 | 0.356 | 0.246 | 0.352 | 0.355 | 0.33 | |
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| 0.042 | 8.0 | 2432 | 2.0781 | 0.481 | 0.264 | 0.169 | 0.2 | 0.421 | 0.261 | 0.403 | 0.421 | 0.431 | |
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| 0.0124 | 9.0 | 2736 | 1.9029 | 0.464 | 0.293 | 0.222 | 0.2 | 0.466 | 0.304 | 0.445 | 0.465 | 0.473 | |
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| 0.0382 | 10.0 | 3040 | 1.9442 | 0.464 | 0.282 | 0.212 | 0.2 | 0.473 | 0.304 | 0.447 | 0.467 | 0.474 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.37.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.15.2 |
