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---
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0260
- Wer Score: 2.5870
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 7.3233 | 2.8571 | 50 | 4.4354 | 22.5705 |
| 2.2055 | 5.7143 | 100 | 0.3490 | 10.2262 |
| 0.1031 | 8.5714 | 150 | 0.0287 | 0.3700 |
| 0.0177 | 11.4286 | 200 | 0.0197 | 1.4176 |
| 0.007 | 14.2857 | 250 | 0.0214 | 4.7060 |
| 0.0029 | 17.1429 | 300 | 0.0232 | 3.8049 |
| 0.0017 | 20.0 | 350 | 0.0237 | 4.6676 |
| 0.0012 | 22.8571 | 400 | 0.0241 | 4.0458 |
| 0.0011 | 25.7143 | 450 | 0.0246 | 3.7335 |
| 0.001 | 28.5714 | 500 | 0.0249 | 3.2042 |
| 0.0011 | 31.4286 | 550 | 0.0253 | 2.9423 |
| 0.0011 | 34.2857 | 600 | 0.0257 | 2.7527 |
| 0.0011 | 37.1429 | 650 | 0.0256 | 2.7015 |
| 0.0011 | 40.0 | 700 | 0.0258 | 2.7152 |
| 0.001 | 42.8571 | 750 | 0.0260 | 2.5531 |
| 0.001 | 45.7143 | 800 | 0.0260 | 2.6126 |
| 0.001 | 48.5714 | 850 | 0.0260 | 2.5870 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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