|
--- |
|
library_name: transformers |
|
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 an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0627 |
|
- Wer Score: 8.5567 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer Score | |
|
|:-------------:|:-------:|:----:|:---------------:|:---------:| |
|
| 2.2863 | 2.1277 | 50 | 0.3771 | 0.4680 | |
|
| 0.1088 | 4.2553 | 100 | 0.0445 | 0.4631 | |
|
| 0.0219 | 6.3830 | 150 | 0.0438 | 0.4483 | |
|
| 0.0152 | 8.5106 | 200 | 0.0437 | 0.4532 | |
|
| 0.0124 | 10.6383 | 250 | 0.0474 | 0.4877 | |
|
| 0.0101 | 12.7660 | 300 | 0.0499 | 2.7241 | |
|
| 0.008 | 14.8936 | 350 | 0.0512 | 4.0493 | |
|
| 0.0064 | 17.0213 | 400 | 0.0535 | 5.2857 | |
|
| 0.0039 | 19.1489 | 450 | 0.0574 | 7.3103 | |
|
| 0.0025 | 21.2766 | 500 | 0.0587 | 7.6847 | |
|
| 0.0015 | 23.4043 | 550 | 0.0620 | 8.0443 | |
|
| 0.0011 | 25.5319 | 600 | 0.0617 | 9.0788 | |
|
| 0.0009 | 27.6596 | 650 | 0.0627 | 8.5567 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.19.1 |
|
|