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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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datasets: |
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- imagefolder |
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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 the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1481 |
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- Wer Score: 7.2150 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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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| 0.0359 | 3.12 | 50 | 0.1192 | 0.8131 | |
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| 0.0174 | 6.25 | 100 | 0.1257 | 3.0654 | |
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| 0.0132 | 9.38 | 150 | 0.1283 | 0.7850 | |
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| 0.011 | 12.5 | 200 | 0.1297 | 1.4112 | |
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| 0.0095 | 15.62 | 250 | 0.1332 | 5.1028 | |
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| 0.0083 | 18.75 | 300 | 0.1376 | 5.5701 | |
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| 0.0077 | 21.88 | 350 | 0.1368 | 0.7944 | |
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| 0.0068 | 25.0 | 400 | 0.1366 | 5.6168 | |
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| 0.0061 | 28.12 | 450 | 0.1417 | 4.4299 | |
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| 0.0057 | 31.25 | 500 | 0.1406 | 6.6636 | |
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| 0.0047 | 34.38 | 550 | 0.1438 | 7.3738 | |
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| 0.0038 | 37.5 | 600 | 0.1448 | 7.6262 | |
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| 0.0032 | 40.62 | 650 | 0.1468 | 9.0841 | |
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| 0.0027 | 43.75 | 700 | 0.1473 | 6.8598 | |
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| 0.0024 | 46.88 | 750 | 0.1480 | 7.3178 | |
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| 0.0021 | 50.0 | 800 | 0.1481 | 7.2150 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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