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--- |
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license: apache-2.0 |
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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: Qwen/Qwen2-7B |
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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: llama2-7B_final_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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# llama2-7B_final_MT |
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This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5523 |
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- Accuracy: 0.8117 |
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- Precision: 0.7913 |
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- Recall: 0.8467 |
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- F1 score: 0.8180 |
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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: 16 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
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| 0.8396 | 0.5 | 200 | 0.8733 | 0.645 | 0.6064 | 0.8267 | 0.6996 | |
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| 0.6541 | 1.0 | 400 | 0.6882 | 0.695 | 0.7127 | 0.6533 | 0.6817 | |
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| 0.4601 | 1.5 | 600 | 0.6691 | 0.7067 | 0.6505 | 0.8933 | 0.7528 | |
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| 0.4437 | 2.0 | 800 | 0.5010 | 0.7833 | 0.7690 | 0.81 | 0.7890 | |
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| 0.3406 | 2.5 | 1000 | 0.5010 | 0.7767 | 0.7823 | 0.7667 | 0.7744 | |
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| 0.2919 | 3.0 | 1200 | 0.4927 | 0.8117 | 0.8127 | 0.81 | 0.8114 | |
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| 0.2219 | 3.5 | 1400 | 0.4971 | 0.8217 | 0.8044 | 0.85 | 0.8266 | |
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| 0.2154 | 4.0 | 1600 | 0.6404 | 0.7633 | 0.7147 | 0.8767 | 0.7874 | |
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| 0.1381 | 4.5 | 1800 | 0.5391 | 0.815 | 0.8 | 0.84 | 0.8195 | |
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| 0.1531 | 5.0 | 2000 | 0.5523 | 0.8117 | 0.7913 | 0.8467 | 0.8180 | |
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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 |
