| | --- |
| | license: mit |
| | base_model: microsoft/git-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | 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 the imagefolder dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0330 |
| | - Wer Score: 1.6516 |
| |
|
| | ## 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: 25 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer Score | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:| |
| | | 7.4022 | 4.17 | 50 | 4.7553 | 21.1384 | |
| | | 2.7988 | 8.33 | 100 | 0.9177 | 10.7623 | |
| | | 0.3496 | 12.5 | 150 | 0.0709 | 2.1170 | |
| | | 0.0373 | 16.67 | 200 | 0.0327 | 1.3170 | |
| | | 0.0142 | 20.83 | 250 | 0.0316 | 1.5031 | |
| | | 0.0069 | 25.0 | 300 | 0.0330 | 1.6516 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.31.0.dev0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| | |
