| | --- |
| | license: mit |
| | base_model: microsoft/git-base |
| | tags: |
| | - generated_from_trainer |
| | 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 None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2324 |
| | - Wer Score: 5.2456 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:| |
| | | 7.3165 | 5.26 | 50 | 4.6355 | 4.8031 | |
| | | 2.6531 | 10.53 | 100 | 0.8536 | 4.2762 | |
| | | 0.4 | 15.79 | 150 | 0.2527 | 4.6248 | |
| | | 0.1634 | 21.05 | 200 | 0.2272 | 4.4392 | |
| | | 0.125 | 26.32 | 250 | 0.2262 | 4.3356 | |
| | | 0.1054 | 31.58 | 300 | 0.2286 | 6.6022 | |
| | | 0.0932 | 36.84 | 350 | 0.2305 | 4.6967 | |
| | | 0.0856 | 42.11 | 400 | 0.2320 | 4.4171 | |
| | | 0.0811 | 47.37 | 450 | 0.2324 | 5.2456 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.36.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.14.7 |
| | - Tokenizers 0.15.0 |
| | |
