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--- |
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license: other |
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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/Qwen1.5-7B |
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metrics: |
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- accuracy |
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model-index: |
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- name: twitter_disaster |
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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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# twitter_disaster |
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This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4902 |
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- Accuracy: 0.7767 |
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- F1 Macro: 0.7451 |
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- F1 Micro: 0.7767 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 32 |
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- total_eval_batch_size: 32 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:| |
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| 0.8422 | 0.18 | 50 | 0.6453 | 0.7178 | 0.6372 | 0.7178 | |
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| 0.6082 | 0.37 | 100 | 0.5489 | 0.7472 | 0.7123 | 0.7472 | |
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| 0.4305 | 0.55 | 150 | 0.5572 | 0.7252 | 0.5777 | 0.7252 | |
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| 0.5021 | 0.74 | 200 | 0.5000 | 0.7721 | 0.7437 | 0.7721 | |
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| 0.4715 | 0.92 | 250 | 0.4902 | 0.7767 | 0.7451 | 0.7767 | |
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| 0.3937 | 1.1 | 300 | 0.5194 | 0.7601 | 0.7018 | 0.7601 | |
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| 0.4219 | 1.29 | 350 | 0.5228 | 0.7665 | 0.7228 | 0.7665 | |
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| 0.4315 | 1.47 | 400 | 0.5791 | 0.7555 | 0.6901 | 0.7555 | |
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| 0.4134 | 1.65 | 450 | 0.6182 | 0.7390 | 0.7196 | 0.7390 | |
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| 0.4173 | 1.84 | 500 | 0.5454 | 0.7638 | 0.7116 | 0.7638 | |
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| 0.3278 | 2.02 | 550 | 0.5477 | 0.7721 | 0.7219 | 0.7721 | |
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| 0.2641 | 2.21 | 600 | 0.6011 | 0.7528 | 0.7152 | 0.7528 | |
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| 0.2256 | 2.39 | 650 | 0.6485 | 0.7601 | 0.6962 | 0.7601 | |
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| 0.2544 | 2.57 | 700 | 0.6459 | 0.7629 | 0.7165 | 0.7629 | |
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| 0.2839 | 2.76 | 750 | 0.5922 | 0.7656 | 0.7253 | 0.7656 | |
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| 0.2634 | 2.94 | 800 | 0.6312 | 0.7638 | 0.7076 | 0.7638 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
