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1-epochs5-char-based-freeze_cnn-dropout0.1
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: 0.1245
- Wer: 0.0865
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: 2e-05
- train_batch_size: 10
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 40
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.8545 | 0.37 | 2500 | 2.8872 | 1.0 |
| 0.7012 | 0.74 | 5000 | 0.3473 | 0.2840 |
| 0.46 | 1.11 | 7500 | 0.2032 | 0.1510 |
| 0.3848 | 1.48 | 10000 | 0.1668 | 0.1194 |
| 0.3535 | 1.85 | 12500 | 0.1518 | 0.1086 |
| 0.3667 | 2.22 | 15000 | 0.1442 | 0.1019 |
| 0.3058 | 2.59 | 17500 | 0.1381 | 0.0961 |
| 0.3026 | 2.96 | 20000 | 0.1327 | 0.0924 |
| 0.2891 | 3.33 | 22500 | 0.1326 | 0.0917 |
| 0.294 | 3.7 | 25000 | 0.1278 | 0.0894 |
| 0.2846 | 4.07 | 27500 | 0.1257 | 0.0885 |
| 0.259 | 4.44 | 30000 | 0.1244 | 0.0874 |
| 0.2348 | 4.81 | 32500 | 0.1245 | 0.0865 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.14.1
