| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: git-base-500img-dataset |
| | 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-500img-dataset |
| |
|
| | 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: 0.4161 |
| | - Wer Score: 2.0379 |
| |
|
| | ## 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: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 50 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer Score | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:| |
| | | 7.0698 | 3.23 | 50 | 4.5086 | 2.5298 | |
| | | 2.6252 | 6.45 | 100 | 0.9823 | 2.2976 | |
| | | 0.5497 | 9.68 | 150 | 0.4681 | 1.6707 | |
| | | 0.2558 | 12.9 | 200 | 0.4162 | 1.7907 | |
| | | 0.1551 | 16.13 | 250 | 0.4052 | 2.0984 | |
| | | 0.1041 | 19.35 | 300 | 0.4054 | 2.0984 | |
| | | 0.0764 | 22.58 | 350 | 0.4088 | 2.0576 | |
| | | 0.0581 | 25.81 | 400 | 0.4054 | 2.0899 | |
| | | 0.0462 | 29.03 | 450 | 0.4092 | 2.0484 | |
| | | 0.0382 | 32.26 | 500 | 0.4118 | 2.1387 | |
| | | 0.0329 | 35.48 | 550 | 0.4126 | 2.1315 | |
| | | 0.0275 | 38.71 | 600 | 0.4139 | 2.0114 | |
| | | 0.0255 | 41.94 | 650 | 0.4173 | 2.0098 | |
| | | 0.0234 | 45.16 | 700 | 0.4155 | 2.0206 | |
| | | 0.0226 | 48.39 | 750 | 0.4161 | 2.0379 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.30.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.3 |
| | - Tokenizers 0.13.3 |
| | |
