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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: working_dir |
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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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# working_dir |
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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: 7.3083 |
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- Wer Score: {'bleu': 0.002242953743170335, 'precisions': [0.00878409616273694, 0.004012964963728971, 0.001545833977430824, 0.00046446818392940084], 'brevity_penalty': 1.0, 'length_ratio': 68.30526315789474, 'translation_length': 6489, 'reference_length': 95} |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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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: 1 |
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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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| 7.9926 | 0.1 | 1 | 7.8580 | {'bleu': 0.0, 'precisions': [0.00648248186448526, 0.0017004173751739063, 0.0006192909119058678, 0.0], 'brevity_penalty': 1.0, 'length_ratio': 68.2, 'translation_length': 6479, 'reference_length': 95} | |
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| 7.8988 | 0.2 | 2 | 7.7407 | {'bleu': 0.0, 'precisions': [0.008140531276778063, 0.002717391304347826, 0.0007161271841879118, 0.0], 'brevity_penalty': 1.0, 'length_ratio': 73.70526315789473, 'translation_length': 7002, 'reference_length': 95} | |
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| 7.8036 | 0.3 | 3 | 7.6263 | {'bleu': 0.0, 'precisions': [0.008062234794908063, 0.002974504249291785, 0.0005673758865248227, 0.0], 'brevity_penalty': 1.0, 'length_ratio': 74.42105263157895, 'translation_length': 7070, 'reference_length': 95} | |
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| 7.7237 | 0.4 | 4 | 7.5370 | {'bleu': 0.0, 'precisions': [0.008338044092707745, 0.003538069629210303, 0.0005668934240362812, 0.0], 'brevity_penalty': 1.0, 'length_ratio': 74.48421052631579, 'translation_length': 7076, 'reference_length': 95} | |
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| 7.5959 | 0.5 | 5 | 7.4688 | {'bleu': 0.001689755477270402, 'precisions': [0.008193247633846589, 0.0035365681143018812, 0.0009916418756197763, 0.0002837281883955171], 'brevity_penalty': 1.0, 'length_ratio': 74.51578947368421, 'translation_length': 7079, 'reference_length': 95} | |
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| 7.545 | 0.6 | 6 | 7.4154 | {'bleu': 0.0016910162898086155, 'precisions': [0.008244994110718492, 0.0032438808611029196, 0.0010336680448907265, 0.0002957704821058858], 'brevity_penalty': 1.0, 'length_ratio': 71.49473684210527, 'translation_length': 6792, 'reference_length': 95} | |
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| 7.5008 | 0.7 | 7 | 7.3736 | {'bleu': 0.0027244361260593537, 'precisions': [0.011021452469986223, 0.004732794320646815, 0.0017783046828689982, 0.000593941793704217], 'brevity_penalty': 1.0, 'length_ratio': 53.48421052631579, 'translation_length': 5081, 'reference_length': 95} | |
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| 7.4952 | 0.8 | 8 | 7.3412 | {'bleu': 0.0026505451685217172, 'precisions': [0.010477941176470587, 0.004604051565377533, 0.0018450184501845018, 0.00055452865064695], 'brevity_penalty': 1.0, 'length_ratio': 57.26315789473684, 'translation_length': 5440, 'reference_length': 95} | |
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| 7.4316 | 0.9 | 9 | 7.3194 | {'bleu': 0.0023042253386690104, 'precisions': [0.009205426356589148, 0.0038822387576835974, 0.0016202203499675956, 0.0004868549172346641], 'brevity_penalty': 1.0, 'length_ratio': 65.17894736842105, 'translation_length': 6192, 'reference_length': 95} | |
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| 7.4141 | 1.0 | 10 | 7.3083 | {'bleu': 0.002242953743170335, 'precisions': [0.00878409616273694, 0.004012964963728971, 0.001545833977430824, 0.00046446818392940084], 'brevity_penalty': 1.0, 'length_ratio': 68.30526315789474, 'translation_length': 6489, 'reference_length': 95} | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.15.2 |
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