wav2vec2-xlsr-53-rm-vallader-with-lm
This model is a fine-tuned version of anuragshas/wav2vec2-large-xlsr-53-rm-vallader on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.4552
- Wer: 0.3206
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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.112
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2379 | 3.12 | 100 | 0.4041 | 0.3396 |
| 0.103 | 6.25 | 200 | 0.4400 | 0.3337 |
| 0.0664 | 9.38 | 300 | 0.4239 | 0.3315 |
| 0.0578 | 12.5 | 400 | 0.4303 | 0.3267 |
| 0.0446 | 15.62 | 500 | 0.4575 | 0.3274 |
| 0.041 | 18.75 | 600 | 0.4451 | 0.3223 |
| 0.0402 | 21.88 | 700 | 0.4507 | 0.3206 |
| 0.0374 | 25.0 | 800 | 0.4649 | 0.3208 |
| 0.0371 | 28.12 | 900 | 0.4552 | 0.3206 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.1
- Tokenizers 0.10.3