WAXAL-mlg_asr-w2v-bert-2.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8135
- Cer: 0.2007
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 3.6449 | 1.7544 | 300 | 0.8086 | 0.2391 |
| 0.5700 | 3.5088 | 600 | 0.7955 | 0.2231 |
| 0.3980 | 5.2632 | 900 | 0.7420 | 0.2109 |
| 0.2475 | 7.0175 | 1200 | 0.7624 | 0.2048 |
| 0.1611 | 8.7719 | 1500 | 0.8076 | 0.2016 |
| 0.1611 | 10.0 | 1710 | 0.8135 | 0.2007 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2