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---
license: mit
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: git-base-pokemon
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# git-base-pokemon
This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0371
- Wer Score: 2.4731
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.3268 | 2.13 | 50 | 4.4847 | 21.4974 |
| 2.2464 | 4.26 | 100 | 0.3519 | 11.4118 |
| 0.1049 | 6.38 | 150 | 0.0302 | 0.7468 |
| 0.0223 | 8.51 | 200 | 0.0270 | 0.4668 |
| 0.0137 | 10.64 | 250 | 0.0280 | 3.5742 |
| 0.0073 | 12.77 | 300 | 0.0304 | 7.1240 |
| 0.0034 | 14.89 | 350 | 0.0309 | 6.4885 |
| 0.0018 | 17.02 | 400 | 0.0326 | 5.0499 |
| 0.0011 | 19.15 | 450 | 0.0335 | 5.2302 |
| 0.0009 | 21.28 | 500 | 0.0342 | 4.3645 |
| 0.0007 | 23.4 | 550 | 0.0346 | 5.1445 |
| 0.0006 | 25.53 | 600 | 0.0351 | 4.0639 |
| 0.0006 | 27.66 | 650 | 0.0355 | 3.8862 |
| 0.0006 | 29.79 | 700 | 0.0359 | 3.4514 |
| 0.0006 | 31.91 | 750 | 0.0363 | 3.0486 |
| 0.0006 | 34.04 | 800 | 0.0363 | 2.8645 |
| 0.0006 | 36.17 | 850 | 0.0366 | 2.7199 |
| 0.0006 | 38.3 | 900 | 0.0369 | 2.6675 |
| 0.0006 | 40.43 | 950 | 0.0369 | 2.6304 |
| 0.0006 | 42.55 | 1000 | 0.0370 | 2.4910 |
| 0.0006 | 44.68 | 1050 | 0.0370 | 2.4834 |
| 0.0006 | 46.81 | 1100 | 0.0371 | 2.4629 |
| 0.0006 | 48.94 | 1150 | 0.0371 | 2.4731 |
### Framework versions
- Transformers 4.29.1
- Pytorch 1.12.1
- Datasets 2.11.0
- Tokenizers 0.11.0
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