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README.md
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---
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license: mit
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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: 0.0407
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- Wer Score: 2.1746
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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: 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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| 7.3192 | 2.13 | 50 | 4.4908 | 21.3506 |
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| 2.2486 | 4.26 | 100 | 0.3526 | 10.3803 |
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| 0.1047 | 6.38 | 150 | 0.0321 | 0.3635 |
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| 0.0222 | 8.51 | 200 | 0.0298 | 0.6636 |
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| 0.0145 | 10.64 | 250 | 0.0286 | 2.1759 |
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| 0.0081 | 12.77 | 300 | 0.0321 | 2.9690 |
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| 0.004 | 14.89 | 350 | 0.0340 | 2.2962 |
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| 0.002 | 17.02 | 400 | 0.0356 | 2.1837 |
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| 0.0012 | 19.15 | 450 | 0.0370 | 3.1501 |
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| 0.0009 | 21.28 | 500 | 0.0379 | 2.5821 |
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| 0.0007 | 23.4 | 550 | 0.0382 | 2.7995 |
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| 0.0006 | 25.53 | 600 | 0.0386 | 2.8318 |
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| 0.0006 | 27.66 | 650 | 0.0387 | 2.4541 |
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| 0.0006 | 29.79 | 700 | 0.0390 | 2.6404 |
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| 0.0006 | 31.91 | 750 | 0.0395 | 2.5614 |
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| 0.0006 | 34.04 | 800 | 0.0395 | 2.5317 |
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| 0.0006 | 36.17 | 850 | 0.0399 | 2.5886 |
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| 0.0006 | 38.3 | 900 | 0.0403 | 2.3829 |
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| 0.0006 | 40.43 | 950 | 0.0404 | 2.2937 |
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| 0.0006 | 42.55 | 1000 | 0.0404 | 2.2173 |
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| 0.0006 | 44.68 | 1050 | 0.0406 | 2.1617 |
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| 0.0006 | 46.81 | 1100 | 0.0406 | 2.1669 |
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| 0.0006 | 48.94 | 1150 | 0.0407 | 2.1746 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 1.13.1
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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