| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/git-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: git-base-isg-288 |
| 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-isg-288 |
|
|
| 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: 0.0937 |
| - Wer Score: 2.7076 |
|
|
| ## 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: Use 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: 100 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer Score | |
| |:-------------:|:-------:|:----:|:---------------:|:---------:| |
| | 13.4828 | 5.5882 | 50 | 4.2850 | 16.7473 | |
| | 3.9992 | 11.1176 | 100 | 0.3655 | 0.7942 | |
| | 0.2368 | 16.7059 | 150 | 0.0692 | 0.6679 | |
| | 0.0533 | 22.2353 | 200 | 0.0733 | 0.7004 | |
| | 0.0339 | 27.8235 | 250 | 0.0765 | 0.8520 | |
| | 0.0249 | 33.3529 | 300 | 0.0795 | 1.8592 | |
| | 0.0165 | 38.9412 | 350 | 0.0821 | 2.3827 | |
| | 0.0074 | 44.4706 | 400 | 0.0861 | 2.0542 | |
| | 0.0034 | 50.0 | 450 | 0.0885 | 3.0361 | |
| | 0.0023 | 55.5882 | 500 | 0.0909 | 2.4946 | |
| | 0.0018 | 61.1176 | 550 | 0.0920 | 2.6426 | |
| | 0.0016 | 66.7059 | 600 | 0.0930 | 2.6354 | |
| | 0.0015 | 72.2353 | 650 | 0.0930 | 2.2527 | |
| | 0.0013 | 77.8235 | 700 | 0.0935 | 2.6859 | |
| | 0.0013 | 83.3529 | 750 | 0.0937 | 2.7726 | |
| | 0.0012 | 88.9412 | 800 | 0.0937 | 2.7076 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.1 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
