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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-clothes |
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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-clothes |
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2143 |
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- Wer Score: 2.4047 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 50 |
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- mixed_precision_training: Native AMP |
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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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| 7.1475 | 3.5714 | 50 | 4.4300 | 0.8516 | |
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| 2.384 | 7.1429 | 100 | 0.6209 | 0.7782 | |
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| 0.3154 | 10.7143 | 150 | 0.2059 | 2.0570 | |
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| 0.1406 | 14.2857 | 200 | 0.1841 | 2.6379 | |
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| 0.0927 | 17.8571 | 250 | 0.1831 | 2.5492 | |
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| 0.062 | 21.4286 | 300 | 0.1891 | 2.6554 | |
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| 0.0423 | 25.0 | 350 | 0.1938 | 2.5195 | |
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| 0.0292 | 28.5714 | 400 | 0.1996 | 2.5295 | |
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| 0.0214 | 32.1429 | 450 | 0.2034 | 2.4541 | |
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| 0.0169 | 35.7143 | 500 | 0.2082 | 2.5956 | |
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| 0.0139 | 39.2857 | 550 | 0.2105 | 2.2852 | |
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| 0.0119 | 42.8571 | 600 | 0.2129 | 2.4300 | |
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| 0.0106 | 46.4286 | 650 | 0.2138 | 2.4355 | |
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| 0.01 | 50.0 | 700 | 0.2143 | 2.4047 | |
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### Framework versions |
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- Transformers 4.48.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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