| | --- |
| | license: mit |
| | base_model: microsoft/git-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | model-index: |
| | - name: git-base-food |
| | 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-food |
| |
|
| | 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: 0.0444 |
| | - Wer Score: 10.0470 |
| |
|
| | ## 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: 2 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 20 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer Score | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:| |
| | | No log | 1.05 | 20 | 7.3069 | 113.3758 | |
| | | No log | 2.11 | 40 | 5.3566 | 3.2282 | |
| | | No log | 3.16 | 60 | 3.4409 | 1.1879 | |
| | | No log | 4.21 | 80 | 1.7218 | 1.1007 | |
| | | No log | 5.26 | 100 | 0.5834 | 1.0872 | |
| | | No log | 6.32 | 120 | 0.1684 | 1.3020 | |
| | | No log | 7.37 | 140 | 0.0720 | 2.9732 | |
| | | No log | 8.42 | 160 | 0.0507 | 2.0805 | |
| | | No log | 9.47 | 180 | 0.0467 | 3.0336 | |
| | | No log | 10.53 | 200 | 0.0415 | 10.6107 | |
| | | No log | 11.58 | 220 | 0.0425 | 7.7383 | |
| | | No log | 12.63 | 240 | 0.0426 | 14.1745 | |
| | | No log | 13.68 | 260 | 0.0434 | 6.0067 | |
| | | No log | 14.74 | 280 | 0.0447 | 10.5503 | |
| | | No log | 15.79 | 300 | 0.0434 | 9.1678 | |
| | | No log | 16.84 | 320 | 0.0439 | 10.8591 | |
| | | No log | 17.89 | 340 | 0.0446 | 10.0470 | |
| | | No log | 18.95 | 360 | 0.0444 | 10.1208 | |
| | | No log | 20.0 | 380 | 0.0444 | 10.0470 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.34.1 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| | |
