output
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2822
- Wer: 0.2423
- Cer: 0.0842
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
I have used dataset other than mozila common voice, thats why for fair evaluation, i do 80:20 split.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 48
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|---|---|---|---|---|---|
| No log | 1.0 | 174 | 0.9860 | 3.1257 | 1.0 |
| No log | 2.0 | 348 | 0.9404 | 2.4914 | 0.9997 |
| No log | 3.0 | 522 | 0.1889 | 0.5970 | 0.5376 |
| No log | 4.0 | 696 | 0.1428 | 0.4462 | 0.4121 |
| No log | 5.0 | 870 | 0.1211 | 0.3775 | 0.3525 |
| 1.7 | 6.0 | 1044 | 0.1113 | 0.3594 | 0.3264 |
| 1.7 | 7.0 | 1218 | 0.1032 | 0.3354 | 0.3013 |
| 1.7 | 8.0 | 1392 | 0.1005 | 0.3171 | 0.2843 |
| 1.7 | 9.0 | 1566 | 0.0953 | 0.3115 | 0.2717 |
| 1.7 | 10.0 | 1740 | 0.0934 | 0.3058 | 0.2671 |
| 1.7 | 11.0 | 1914 | 0.0926 | 0.3060 | 0.2656 |
| 0.3585 | 12.0 | 2088 | 0.0899 | 0.3070 | 0.2566 |
| 0.3585 | 13.0 | 2262 | 0.0888 | 0.2979 | 0.2509 |
| 0.3585 | 14.0 | 2436 | 0.0868 | 0.3005 | 0.2473 |
| 0.3585 | 15.0 | 2610 | 0.2822 | 0.2423 | 0.0842 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0
- Datasets 2.4.0
- Tokenizers 0.12.1