ssc-ttj-mms-model-mix-adapt-max
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1838
- Cer: 0.0697
- Wer: 0.3887
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: 0.001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 0.2793 | 0.5579 | 200 | 0.2131 | 0.0742 | 0.4136 |
| 0.2597 | 1.1144 | 400 | 0.2044 | 0.0752 | 0.4150 |
| 0.2649 | 1.6722 | 600 | 0.1958 | 0.0722 | 0.4004 |
| 0.259 | 2.2287 | 800 | 0.1909 | 0.0712 | 0.3978 |
| 0.2284 | 2.7866 | 1000 | 0.1912 | 0.0707 | 0.3946 |
| 0.2333 | 3.3431 | 1200 | 0.1899 | 0.0712 | 0.3981 |
| 0.2096 | 3.9010 | 1400 | 0.1867 | 0.0700 | 0.3902 |
| 0.2226 | 4.4575 | 1600 | 0.1838 | 0.0697 | 0.3887 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.0