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git-base-pokemon

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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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+
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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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+
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+ # git-base-pokemon
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+
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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: 0.0429
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+ - Wer Score: 1.9591
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|
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+ | 7.3666 | 1.06 | 50 | 4.4430 | 21.5287 |
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+ | 2.1581 | 2.13 | 100 | 0.2911 | 0.9783 |
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+ | 0.0896 | 3.19 | 150 | 0.0328 | 0.3665 |
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+ | 0.0269 | 4.26 | 200 | 0.0274 | 0.3487 |
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+ | 0.0208 | 5.32 | 250 | 0.0284 | 0.4189 |
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+ | 0.0168 | 6.38 | 300 | 0.0287 | 1.1673 |
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+ | 0.0133 | 7.45 | 350 | 0.0296 | 6.0881 |
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+ | 0.0106 | 8.51 | 400 | 0.0306 | 1.7969 |
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+ | 0.0076 | 9.57 | 450 | 0.0322 | 7.1852 |
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+ | 0.0053 | 10.64 | 500 | 0.0329 | 14.8889 |
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+ | 0.0039 | 11.7 | 550 | 0.0338 | 12.2720 |
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+ | 0.0027 | 12.77 | 600 | 0.0356 | 5.1533 |
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+ | 0.0016 | 13.83 | 650 | 0.0371 | 8.4253 |
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+ | 0.001 | 14.89 | 700 | 0.0379 | 6.7344 |
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+ | 0.0006 | 15.96 | 750 | 0.0385 | 7.7586 |
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+ | 0.0005 | 17.02 | 800 | 0.0392 | 9.0294 |
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+ | 0.0004 | 18.09 | 850 | 0.0385 | 7.5083 |
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+ | 0.0004 | 19.15 | 900 | 0.0394 | 5.1188 |
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+ | 0.0004 | 20.21 | 950 | 0.0397 | 5.0600 |
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+ | 0.0004 | 21.28 | 1000 | 0.0399 | 4.4125 |
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+ | 0.0003 | 22.34 | 1050 | 0.0405 | 3.7803 |
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+ | 0.0003 | 23.4 | 1100 | 0.0406 | 3.3397 |
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+ | 0.0003 | 24.47 | 1150 | 0.0408 | 3.3218 |
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+ | 0.0003 | 25.53 | 1200 | 0.0411 | 2.8212 |
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+ | 0.0003 | 26.6 | 1250 | 0.0411 | 2.7165 |
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+ | 0.0003 | 27.66 | 1300 | 0.0414 | 2.7625 |
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+ | 0.0003 | 28.72 | 1350 | 0.0416 | 2.4330 |
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+ | 0.0003 | 29.79 | 1400 | 0.0416 | 2.2350 |
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+ | 0.0003 | 30.85 | 1450 | 0.0419 | 2.1699 |
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+ | 0.0003 | 31.91 | 1500 | 0.0421 | 2.0026 |
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+ | 0.0003 | 32.98 | 1550 | 0.0420 | 2.1609 |
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+ | 0.0003 | 34.04 | 1600 | 0.0421 | 2.0307 |
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+ | 0.0003 | 35.11 | 1650 | 0.0422 | 1.9668 |
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+ | 0.0003 | 36.17 | 1700 | 0.0423 | 1.9387 |
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+ | 0.0003 | 37.23 | 1750 | 0.0425 | 1.9464 |
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+ | 0.0003 | 38.3 | 1800 | 0.0427 | 1.8761 |
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+ | 0.0003 | 39.36 | 1850 | 0.0427 | 1.8940 |
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+ | 0.0003 | 40.43 | 1900 | 0.0428 | 1.9068 |
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+ | 0.0003 | 41.49 | 1950 | 0.0428 | 1.8774 |
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+ | 0.0003 | 42.55 | 2000 | 0.0429 | 1.8352 |
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+ | 0.0002 | 43.62 | 2050 | 0.0428 | 2.0907 |
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+ | 0.0002 | 44.68 | 2100 | 0.0429 | 2.0319 |
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+ | 0.0002 | 45.74 | 2150 | 0.0429 | 2.0179 |
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+ | 0.0002 | 46.81 | 2200 | 0.0429 | 1.9706 |
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+ | 0.0002 | 47.87 | 2250 | 0.0429 | 1.9604 |
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+ | 0.0002 | 48.94 | 2300 | 0.0429 | 1.9540 |
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+ | 0.0002 | 50.0 | 2350 | 0.0429 | 1.9591 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.0
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+ - Pytorch 2.0.0+cu118
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+ - Datasets 2.11.0
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+ - Tokenizers 0.13.3