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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: meta-llama/Llama-2-13b-hf |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: llama2-13B_MT |
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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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# llama2-13B_MT |
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This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5717 |
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- Accuracy: 0.7967 |
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- Precision: 0.8296 |
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- Recall: 0.7467 |
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- F1 score: 0.7860 |
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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: 0.0001 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 score | Precision | Recall | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:--------:|:---------:|:------:|:---------------:| |
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| 0.6169 | 0.25 | 200 | 0.735 | 0.7145 | 0.7743 | 0.6633 | 0.5712 | |
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| 0.5218 | 0.5 | 400 | 0.765 | 0.7487 | 0.8046 | 0.7 | 0.5406 | |
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| 0.4976 | 0.75 | 600 | 0.7717 | 0.7486 | 0.8327 | 0.68 | 0.4991 | |
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| 0.4531 | 1.0 | 800 | 0.7567 | 0.7045 | 0.8969 | 0.58 | 0.5727 | |
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| 0.339 | 1.25 | 1000 | 0.6176 | 0.7617 | 0.9198 | 0.5733 | 0.7064 | |
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| 0.3046 | 1.5 | 1200 | 0.5150 | 0.7767 | 0.7964 | 0.7433 | 0.7690 | |
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| 0.3363 | 1.75 | 1400 | 0.5185 | 0.795 | 0.8554 | 0.71 | 0.7760 | |
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| 0.3074 | 2.0 | 1600 | 0.4635 | 0.79 | 0.7862 | 0.7967 | 0.7914 | |
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| 0.2052 | 2.25 | 1800 | 0.5411 | 0.8 | 0.8659 | 0.71 | 0.7802 | |
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| 0.1841 | 2.5 | 2000 | 0.5959 | 0.8033 | 0.8889 | 0.6933 | 0.7790 | |
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| 0.1629 | 2.75 | 2200 | 0.5510 | 0.7933 | 0.8143 | 0.76 | 0.7862 | |
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| 0.1559 | 3.0 | 2400 | 0.5717 | 0.7967 | 0.8296 | 0.7467 | 0.7860 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.44.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
