exp23-directfit-unfrozen
This model is a fine-tuned version of cyttic/exp22-exp2warm-directfit-frozen on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4588
- Cer: 0.0245
- Wer: 0.0647
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 1.2577 | 0.0424 | 2500 | 1.3378 | 0.1416 | 0.2986 |
| 1.0413 | 0.0848 | 5000 | 1.2441 | 0.1150 | 0.2561 |
| 0.8436 | 0.1272 | 7500 | 1.0854 | 0.0917 | 0.2106 |
| 0.7762 | 0.1696 | 10000 | 0.9314 | 0.0735 | 0.1700 |
| 0.7096 | 0.2120 | 12500 | 0.8954 | 0.0627 | 0.1534 |
| 0.6205 | 0.2544 | 15000 | 0.7907 | 0.0550 | 0.1378 |
| 0.5873 | 0.2968 | 17500 | 0.7408 | 0.0486 | 0.1215 |
| 0.5504 | 0.3392 | 20000 | 0.6894 | 0.0427 | 0.1112 |
| 0.4826 | 0.3816 | 22500 | 0.6537 | 0.0406 | 0.1042 |
| 0.5224 | 0.4240 | 25000 | 0.6245 | 0.0380 | 0.0965 |
| 0.4430 | 0.4664 | 27500 | 0.5866 | 0.0366 | 0.0933 |
| 0.4219 | 0.5088 | 30000 | 0.5724 | 0.0340 | 0.0873 |
| 0.3557 | 0.5512 | 32500 | 0.5586 | 0.0318 | 0.0849 |
| 0.3866 | 0.5936 | 35000 | 0.5399 | 0.0328 | 0.0845 |
| 0.3586 | 0.6360 | 37500 | 0.5267 | 0.0305 | 0.0793 |
| 0.4009 | 0.6784 | 40000 | 0.5082 | 0.0301 | 0.0769 |
| 0.3140 | 0.7208 | 42500 | 0.5011 | 0.0289 | 0.0740 |
| 0.3435 | 0.7632 | 45000 | 0.4874 | 0.0276 | 0.0725 |
| 0.3141 | 0.8056 | 47500 | 0.4807 | 0.0267 | 0.0691 |
| 0.3200 | 0.8480 | 50000 | 0.4738 | 0.0267 | 0.0687 |
| 0.3201 | 0.8904 | 52500 | 0.4682 | 0.0250 | 0.0664 |
| 0.3314 | 0.9328 | 55000 | 0.4633 | 0.0249 | 0.0652 |
| 0.3427 | 0.9752 | 57500 | 0.4604 | 0.0244 | 0.0648 |
| 0.3020 | 1.0 | 58962 | 0.4588 | 0.0245 | 0.0647 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2