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--- |
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base_model: NousResearch/Llama-2-7b-hf |
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library_name: peft |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Ip_test_3000 |
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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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# Ip_test_3000 |
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This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6617 |
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- Accuracy: 0.6013 |
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- Precision: 0.5938 |
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- Recall: 0.6210 |
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- F1: 0.6071 |
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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: 5e-05 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 160 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 0.96 | 21 | 1.1577 | 0.504 | 0.0 | 0.0 | 0.0 | |
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| No log | 1.96 | 42 | 0.9227 | 0.504 | 0.0 | 0.0 | 0.0 | |
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| No log | 2.96 | 63 | 0.6936 | 0.5147 | 0.5108 | 0.5081 | 0.5094 | |
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| No log | 3.96 | 84 | 0.6954 | 0.496 | 0.4423 | 0.0618 | 0.1085 | |
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| No log | 4.96 | 105 | 0.6898 | 0.56 | 0.5453 | 0.6801 | 0.6053 | |
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| No log | 5.96 | 126 | 0.6880 | 0.5653 | 0.5676 | 0.5188 | 0.5421 | |
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| No log | 6.96 | 147 | 0.6856 | 0.5627 | 0.5780 | 0.4382 | 0.4985 | |
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| 13.66 | 7.96 | 168 | 0.6873 | 0.5573 | 0.5369 | 0.7823 | 0.6368 | |
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| 13.66 | 8.96 | 189 | 0.6793 | 0.5893 | 0.5741 | 0.6667 | 0.6169 | |
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| 13.66 | 9.96 | 210 | 0.6777 | 0.584 | 0.5704 | 0.6532 | 0.6090 | |
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| 13.66 | 10.96 | 231 | 0.6690 | 0.6133 | 0.5981 | 0.6720 | 0.6329 | |
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| 13.66 | 11.96 | 252 | 0.6959 | 0.5747 | 0.7087 | 0.2419 | 0.3607 | |
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| 13.66 | 12.96 | 273 | 0.6691 | 0.6093 | 0.6010 | 0.6317 | 0.6160 | |
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| 13.66 | 13.96 | 294 | 0.6689 | 0.5987 | 0.5843 | 0.6613 | 0.6204 | |
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| 10.9484 | 14.96 | 315 | 0.6635 | 0.6 | 0.5984 | 0.5887 | 0.5935 | |
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| 10.9484 | 15.96 | 336 | 0.6617 | 0.6013 | 0.5938 | 0.6210 | 0.6071 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.47.1 |
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- Pytorch 2.3.1.post300 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
