| | --- |
| | license: mit |
| | 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: 0.0345 |
| | - Wer Score: 2.4097 |
| |
|
| | ## 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: 50 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer Score | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:| |
| | | 7.3695 | 4.17 | 50 | 4.5700 | 21.4160 | |
| | | 2.3984 | 8.33 | 100 | 0.4696 | 10.9249 | |
| | | 0.1439 | 12.5 | 150 | 0.0305 | 1.1692 | |
| | | 0.02 | 16.67 | 200 | 0.0263 | 1.5229 | |
| | | 0.0084 | 20.83 | 250 | 0.0295 | 2.6539 | |
| | | 0.003 | 25.0 | 300 | 0.0324 | 3.2125 | |
| | | 0.0018 | 29.17 | 350 | 0.0329 | 2.6628 | |
| | | 0.0014 | 33.33 | 400 | 0.0336 | 2.5407 | |
| | | 0.0013 | 37.5 | 450 | 0.0338 | 2.4008 | |
| | | 0.0011 | 41.67 | 500 | 0.0344 | 2.5115 | |
| | | 0.0011 | 45.83 | 550 | 0.0344 | 2.3766 | |
| | | 0.0011 | 50.0 | 600 | 0.0345 | 2.4097 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.27.4 |
| | - Pytorch 1.13.1+cu116 |
| | - Datasets 2.11.0 |
| | - Tokenizers 0.13.2 |
| | |
