---
library_name: transformers
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
model-index:
- name: git-base-500
  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-500

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: 0.4804
- Wer Score: 8.3286

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Score |
|:-------------:|:------:|:----:|:---------------:|:---------:|
| 3.6377        | 0.8    | 50   | 4.5566          | 8.9044    |
| 1.224         | 1.592  | 100  | 0.7253          | 1.1039    |
| 0.2503        | 2.384  | 150  | 0.4574          | 0.9295    |
| 0.2197        | 3.176  | 200  | 0.4328          | 1.8787    |
| 0.1877        | 3.976  | 250  | 0.4220          | 1.2766    |
| 0.1712        | 4.768  | 300  | 0.4191          | 5.0394    |
| 0.1551        | 5.5600 | 350  | 0.4194          | 3.4952    |
| 0.1555        | 6.352  | 400  | 0.4185          | 3.5920    |
| 0.1405        | 7.144  | 450  | 0.4188          | 8.9391    |
| 0.1339        | 7.944  | 500  | 0.4157          | 3.1930    |
| 0.1236        | 8.736  | 550  | 0.4161          | 3.3608    |
| 0.1179        | 9.528  | 600  | 0.4179          | 4.5639    |
| 0.1143        | 10.32  | 650  | 0.4203          | 7.8746    |
| 0.0984        | 11.112 | 700  | 0.4218          | 3.6105    |
| 0.0977        | 11.912 | 750  | 0.4210          | 6.4683    |
| 0.0896        | 12.704 | 800  | 0.4242          | 8.9421    |
| 0.0876        | 13.496 | 850  | 0.4268          | 6.4528    |
| 0.0791        | 14.288 | 900  | 0.4296          | 8.9367    |
| 0.0861        | 15.08  | 950  | 0.4295          | 8.9462    |
| 0.0713        | 15.88  | 1000 | 0.4345          | 5.5215    |
| 0.0706        | 16.672 | 1050 | 0.4319          | 8.9839    |
| 0.0659        | 17.464 | 1100 | 0.4378          | 7.1995    |
| 0.0633        | 18.256 | 1150 | 0.4366          | 8.9056    |
| 0.0612        | 19.048 | 1200 | 0.4425          | 7.9755    |
| 0.0601        | 19.848 | 1250 | 0.4428          | 7.8967    |
| 0.054         | 20.64  | 1300 | 0.4432          | 8.9534    |
| 0.053         | 21.432 | 1350 | 0.4470          | 8.7013    |
| 0.0528        | 22.224 | 1400 | 0.4489          | 7.5454    |
| 0.0522        | 23.016 | 1450 | 0.4488          | 4.6481    |
| 0.0471        | 23.816 | 1500 | 0.4528          | 8.6278    |
| 0.0458        | 24.608 | 1550 | 0.4552          | 8.7969    |
| 0.0414        | 25.4   | 1600 | 0.4549          | 8.6983    |
| 0.0415        | 26.192 | 1650 | 0.4553          | 5.8256    |
| 0.0398        | 26.992 | 1700 | 0.4584          | 7.7479    |
| 0.0395        | 27.784 | 1750 | 0.4587          | 8.6667    |
| 0.0359        | 28.576 | 1800 | 0.4622          | 8.4624    |
| 0.0347        | 29.368 | 1850 | 0.4610          | 6.7873    |
| 0.034         | 30.16  | 1900 | 0.4634          | 8.4725    |
| 0.0328        | 30.96  | 1950 | 0.4655          | 8.4480    |
| 0.0322        | 31.752 | 2000 | 0.4658          | 8.4839    |
| 0.0301        | 32.544 | 2050 | 0.4655          | 8.4976    |
| 0.0308        | 33.336 | 2100 | 0.4673          | 4.3256    |
| 0.0275        | 34.128 | 2150 | 0.4699          | 7.0305    |
| 0.0286        | 34.928 | 2200 | 0.4708          | 4.2640    |
| 0.0277        | 35.72  | 2250 | 0.4722          | 8.4534    |
| 0.0279        | 36.512 | 2300 | 0.4712          | 8.4665    |
| 0.0262        | 37.304 | 2350 | 0.4723          | 5.3303    |
| 0.026         | 38.096 | 2400 | 0.4735          | 8.4020    |
| 0.0241        | 38.896 | 2450 | 0.4750          | 8.4779    |
| 0.0241        | 39.688 | 2500 | 0.4750          | 8.4194    |
| 0.024         | 40.48  | 2550 | 0.4765          | 7.0854    |
| 0.0226        | 41.272 | 2600 | 0.4788          | 8.4164    |
| 0.0215        | 42.064 | 2650 | 0.4766          | 3.8375    |
| 0.0227        | 42.864 | 2700 | 0.4768          | 3.4355    |
| 0.0223        | 43.656 | 2750 | 0.4770          | 3.7461    |
| 0.0211        | 44.448 | 2800 | 0.4780          | 4.7300    |
| 0.0222        | 45.24  | 2850 | 0.4785          | 3.8919    |
| 0.0211        | 46.032 | 2900 | 0.4796          | 7.5161    |
| 0.02          | 46.832 | 2950 | 0.4797          | 7.9827    |
| 0.0212        | 47.624 | 3000 | 0.4797          | 8.0400    |
| 0.0202        | 48.416 | 3050 | 0.4807          | 8.3190    |
| 0.02          | 49.208 | 3100 | 0.4799          | 8.3375    |
| 0.0206        | 50.0   | 3150 | 0.4804          | 8.3286    |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2