| --- |
| license: mit |
| base_model: microsoft/git-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: git-base-naruto |
| 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-naruto |
|
|
| 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: 0.0613 |
| - Wer Score: 4.6462 |
|
|
| ## 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: 2 |
| - total_train_batch_size: 4 |
| - 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 | |
| |:-------------:|:-------:|:----:|:---------------:|:---------:| |
| | 7.3247 | 3.7037 | 50 | 4.4756 | 6.1692 | |
| | 2.2782 | 7.4074 | 100 | 0.4117 | 0.4308 | |
| | 0.1182 | 11.1111 | 150 | 0.0433 | 0.4462 | |
| | 0.0162 | 14.8148 | 200 | 0.0483 | 0.5231 | |
| | 0.0105 | 18.5185 | 250 | 0.0527 | 0.5231 | |
| | 0.0085 | 22.2222 | 300 | 0.0548 | 0.4769 | |
| | 0.007 | 25.9259 | 350 | 0.0578 | 0.8923 | |
| | 0.006 | 29.6296 | 400 | 0.0599 | 0.8462 | |
| | 0.0051 | 33.3333 | 450 | 0.0598 | 6.0 | |
| | 0.004 | 37.0370 | 500 | 0.0608 | 5.5538 | |
| | 0.0035 | 40.7407 | 550 | 0.0606 | 7.7077 | |
| | 0.0028 | 44.4444 | 600 | 0.0611 | 5.4308 | |
| | 0.0023 | 48.1481 | 650 | 0.0613 | 4.6462 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.2 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
| |
