wav2vec2-E50_feq_speed2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.2476
- Cer: 85.2526
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch 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: 50
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 48.4957 | 0.1289 | 200 | 6.8888 | 100.0 |
| 20.9588 | 0.2579 | 400 | 4.8707 | 97.5029 |
| 13.3764 | 0.3868 | 600 | 4.5300 | 91.7685 |
| 15.9565 | 0.5158 | 800 | 4.5414 | 92.9553 |
| 11.0676 | 0.6447 | 1000 | 4.6375 | 93.8367 |
| 5.7987 | 0.7737 | 1200 | 4.4724 | 93.2902 |
| 4.9382 | 0.9026 | 1400 | 4.4337 | 93.8543 |
| 7.107 | 1.0316 | 1600 | 4.4191 | 93.6428 |
| 5.0628 | 1.1605 | 1800 | 4.4137 | 94.3184 |
| 6.2941 | 1.2895 | 2000 | 4.4307 | 93.0317 |
| 5.6561 | 1.4184 | 2200 | 4.3684 | 93.0905 |
| 5.6863 | 1.5474 | 2400 | 4.3545 | 91.8743 |
| 5.9443 | 1.6763 | 2600 | 4.3462 | 91.3925 |
| 5.3199 | 1.8053 | 2800 | 4.3394 | 90.0823 |
| 5.9598 | 1.9342 | 3000 | 4.3221 | 90.0353 |
| 5.5016 | 2.0632 | 3200 | 4.3175 | 90.3055 |
| 5.7831 | 2.1921 | 3400 | 4.3053 | 89.9236 |
| 4.7223 | 2.3211 | 3600 | 4.2815 | 89.1657 |
| 5.0472 | 2.4500 | 3800 | 4.2367 | 88.4548 |
| 4.835 | 2.5790 | 4000 | 4.2107 | 85.7168 |
| 4.6838 | 2.7079 | 4200 | 4.2758 | 89.1833 |
| 4.7761 | 2.8369 | 4400 | 4.2710 | 85.8813 |
| 4.8559 | 2.9658 | 4600 | 4.2476 | 85.2526 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3