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--- |
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library_name: transformers |
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license: mit |
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base_model: microsoft/git-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: git-base-isg-288 |
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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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# git-base-isg-288 |
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0937 |
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- Wer Score: 2.7076 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Use 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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Score | |
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|:-------------:|:-------:|:----:|:---------------:|:---------:| |
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| 13.4828 | 5.5882 | 50 | 4.2850 | 16.7473 | |
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| 3.9992 | 11.1176 | 100 | 0.3655 | 0.7942 | |
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| 0.2368 | 16.7059 | 150 | 0.0692 | 0.6679 | |
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| 0.0533 | 22.2353 | 200 | 0.0733 | 0.7004 | |
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| 0.0339 | 27.8235 | 250 | 0.0765 | 0.8520 | |
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| 0.0249 | 33.3529 | 300 | 0.0795 | 1.8592 | |
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| 0.0165 | 38.9412 | 350 | 0.0821 | 2.3827 | |
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| 0.0074 | 44.4706 | 400 | 0.0861 | 2.0542 | |
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| 0.0034 | 50.0 | 450 | 0.0885 | 3.0361 | |
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| 0.0023 | 55.5882 | 500 | 0.0909 | 2.4946 | |
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| 0.0018 | 61.1176 | 550 | 0.0920 | 2.6426 | |
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| 0.0016 | 66.7059 | 600 | 0.0930 | 2.6354 | |
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| 0.0015 | 72.2353 | 650 | 0.0930 | 2.2527 | |
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| 0.0013 | 77.8235 | 700 | 0.0935 | 2.6859 | |
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| 0.0013 | 83.3529 | 750 | 0.0937 | 2.7726 | |
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| 0.0012 | 88.9412 | 800 | 0.0937 | 2.7076 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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