git-base-pokemon
This model is a fine-tuned version of microsoft/git-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0350
- Wer Score: 2.2148
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Score |
---|---|---|---|---|
7.3616 | 4.17 | 50 | 4.5895 | 21.4258 |
2.4353 | 8.33 | 100 | 0.4961 | 9.9322 |
0.1527 | 12.5 | 150 | 0.0303 | 1.3197 |
0.0192 | 16.67 | 200 | 0.0260 | 1.3299 |
0.007 | 20.83 | 250 | 0.0297 | 2.2059 |
0.0027 | 25.0 | 300 | 0.0321 | 2.4795 |
0.0017 | 29.17 | 350 | 0.0334 | 2.4488 |
0.0014 | 33.33 | 400 | 0.0340 | 2.1355 |
0.0013 | 37.5 | 450 | 0.0345 | 2.3619 |
0.0012 | 41.67 | 500 | 0.0349 | 2.2084 |
0.0011 | 45.83 | 550 | 0.0350 | 2.1803 |
0.0011 | 50.0 | 600 | 0.0350 | 2.2148 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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