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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Qwen/Qwen2-1.5B |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: fine_tuned_sci_gen_callback10 |
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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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# fine_tuned_sci_gen_callback10 |
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This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1471 |
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- Accuracy: 0.9736 |
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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: 2e-05 |
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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: 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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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.8103 | 0.0384 | 100 | 0.4049 | 0.8802 | |
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| 0.3921 | 0.0769 | 200 | 0.4732 | 0.9001 | |
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| 0.4581 | 0.1153 | 300 | 0.2876 | 0.9256 | |
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| 0.2995 | 0.1537 | 400 | 0.3032 | 0.9313 | |
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| 0.2645 | 0.1922 | 500 | 0.3322 | 0.9334 | |
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| 0.2994 | 0.2306 | 600 | 0.1808 | 0.9494 | |
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| 0.2834 | 0.2690 | 700 | 0.2584 | 0.9464 | |
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| 0.3254 | 0.3075 | 800 | 0.2653 | 0.9408 | |
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| 0.2211 | 0.3459 | 900 | 0.1439 | 0.9585 | |
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| 0.1954 | 0.3843 | 1000 | 0.1905 | 0.9520 | |
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| 0.2486 | 0.4228 | 1100 | 0.2971 | 0.9321 | |
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| 0.1363 | 0.4612 | 1200 | 0.2809 | 0.9386 | |
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| 0.2191 | 0.4996 | 1300 | 0.2436 | 0.9477 | |
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| 0.2003 | 0.5380 | 1400 | 0.1320 | 0.9667 | |
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| 0.1653 | 0.5765 | 1500 | 0.1779 | 0.9602 | |
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| 0.1465 | 0.6149 | 1600 | 0.1386 | 0.9650 | |
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| 0.1698 | 0.6533 | 1700 | 0.1004 | 0.9663 | |
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| 0.1545 | 0.6918 | 1800 | 0.1772 | 0.9598 | |
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| 0.1633 | 0.7302 | 1900 | 0.1856 | 0.9555 | |
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| 0.1889 | 0.7686 | 2000 | 0.1754 | 0.9680 | |
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| 0.214 | 0.8071 | 2100 | 0.1801 | 0.9503 | |
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| 0.1636 | 0.8455 | 2200 | 0.1771 | 0.9641 | |
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| 0.1469 | 0.8839 | 2300 | 0.1493 | 0.9650 | |
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| 0.195 | 0.9224 | 2400 | 0.1066 | 0.9693 | |
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| 0.1109 | 0.9608 | 2500 | 0.1461 | 0.9684 | |
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| 0.1544 | 0.9992 | 2600 | 0.1412 | 0.9650 | |
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| 0.0386 | 1.0377 | 2700 | 0.1471 | 0.9736 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu126 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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