exp26-composed-stage1-frozen
This model is a fine-tuned version of cyttic/exp2-frozen-benyehuda-cont on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4017
- Cer: 0.3913
- Wer: 0.6601
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: 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: 0.05
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 4.0410 | 0.1533 | 2500 | 3.6620 | 0.5444 | 0.8565 |
| 3.4861 | 0.3065 | 5000 | 3.2243 | 0.4949 | 0.7929 |
| 3.2082 | 0.4598 | 7500 | 2.8709 | 0.4577 | 0.7558 |
| 2.8683 | 0.6130 | 10000 | 2.7565 | 0.4322 | 0.7055 |
| 2.6964 | 0.7663 | 12500 | 2.5223 | 0.4108 | 0.6962 |
| 2.6825 | 0.9195 | 15000 | 2.4180 | 0.3921 | 0.6624 |
| 2.6582 | 1.0 | 16313 | 2.4017 | 0.3913 | 0.6601 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2