metadata
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: WMAC1
results: []
WMAC1
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2915
- Wer: 47.7090
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_steps: 650
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.1976 | 0.4757 | 1000 | 0.5681 | 68.4004 |
| 1.3001 | 0.9514 | 2000 | 0.3560 | 52.8999 |
| 0.9103 | 1.4267 | 3000 | 0.3106 | 49.7007 |
| 0.6961 | 1.9024 | 4000 | 0.2851 | 46.8008 |
| 0.5684 | 2.3777 | 5000 | 0.2915 | 47.7090 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2