<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
wav2vec2-large-xlsr-53-torgo-demo-m01-nolm
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: 0.0161
- Wer: 0.4768
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.3987 | 0.9 | 500 | 4.6666 | 1.0 |
| 2.9362 | 1.8 | 1000 | 3.2475 | 1.0 |
| 2.7871 | 2.7 | 1500 | 2.9266 | 1.0 |
| 2.3782 | 3.6 | 2000 | 2.2303 | 1.1786 |
| 1.4728 | 4.5 | 2500 | 1.1054 | 1.2930 |
| 1.0335 | 5.41 | 3000 | 0.6886 | 1.1068 |
| 0.7658 | 6.31 | 3500 | 0.4544 | 0.9401 |
| 0.633 | 7.21 | 4000 | 0.3153 | 0.8427 |
| 0.5852 | 8.11 | 4500 | 0.2553 | 0.7724 |
| 0.4882 | 9.01 | 5000 | 0.2212 | 0.7450 |
| 0.4167 | 9.91 | 5500 | 0.1687 | 0.7014 |
| 0.3897 | 10.81 | 6000 | 0.1433 | 0.6791 |
| 0.382 | 11.71 | 6500 | 0.1249 | 0.6434 |
| 0.3367 | 12.61 | 7000 | 0.1056 | 0.6198 |
| 0.2897 | 13.51 | 7500 | 0.0988 | 0.6172 |
| 0.2457 | 14.41 | 8000 | 0.0885 | 0.5895 |
| 0.243 | 15.32 | 8500 | 0.0759 | 0.5850 |
| 0.2594 | 16.22 | 9000 | 0.0621 | 0.5615 |
| 0.2461 | 17.12 | 9500 | 0.0583 | 0.5470 |
| 0.2307 | 18.02 | 10000 | 0.0501 | 0.5449 |
| 0.2333 | 18.92 | 10500 | 0.0510 | 0.5332 |
| 0.1579 | 19.82 | 11000 | 0.0447 | 0.5295 |
| 0.2097 | 20.72 | 11500 | 0.0392 | 0.5246 |
| 0.1661 | 21.62 | 12000 | 0.0360 | 0.5075 |
| 0.1576 | 22.52 | 12500 | 0.0287 | 0.5076 |
| 0.1452 | 23.42 | 13000 | 0.0253 | 0.4988 |
| 0.1316 | 24.32 | 13500 | 0.0220 | 0.4863 |
| 0.1521 | 25.23 | 14000 | 0.0222 | 0.4865 |
| 0.1319 | 26.13 | 14500 | 0.0187 | 0.4810 |
| 0.1392 | 27.03 | 15000 | 0.0170 | 0.4809 |
| 0.1619 | 27.93 | 15500 | 0.0171 | 0.4777 |
| 0.1374 | 28.83 | 16000 | 0.0164 | 0.4766 |
| 0.1081 | 29.73 | 16500 | 0.0161 | 0.4768 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.0.0
- Tokenizers 0.13.2
