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--- |
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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-pokemon |
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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-pokemon |
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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: 0.0260 |
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- Wer Score: 2.5870 |
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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: 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: 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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| 7.3233 | 2.8571 | 50 | 4.4354 | 22.5705 | |
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| 2.2055 | 5.7143 | 100 | 0.3490 | 10.2262 | |
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| 0.1031 | 8.5714 | 150 | 0.0287 | 0.3700 | |
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| 0.0177 | 11.4286 | 200 | 0.0197 | 1.4176 | |
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| 0.007 | 14.2857 | 250 | 0.0214 | 4.7060 | |
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| 0.0029 | 17.1429 | 300 | 0.0232 | 3.8049 | |
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| 0.0017 | 20.0 | 350 | 0.0237 | 4.6676 | |
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| 0.0012 | 22.8571 | 400 | 0.0241 | 4.0458 | |
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| 0.0011 | 25.7143 | 450 | 0.0246 | 3.7335 | |
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| 0.001 | 28.5714 | 500 | 0.0249 | 3.2042 | |
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| 0.0011 | 31.4286 | 550 | 0.0253 | 2.9423 | |
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| 0.0011 | 34.2857 | 600 | 0.0257 | 2.7527 | |
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| 0.0011 | 37.1429 | 650 | 0.0256 | 2.7015 | |
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| 0.0011 | 40.0 | 700 | 0.0258 | 2.7152 | |
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| 0.001 | 42.8571 | 750 | 0.0260 | 2.5531 | |
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| 0.001 | 45.7143 | 800 | 0.0260 | 2.6126 | |
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| 0.001 | 48.5714 | 850 | 0.0260 | 2.5870 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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