<!-- 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-demo-M01-2
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: 1.8002
- Wer: 0.9717
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: 1000
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 23.0778 | 0.9 | 500 | 3.3183 | 1.0 |
| 3.3341 | 1.8 | 1000 | 3.1046 | 1.0 |
| 2.8465 | 2.7 | 1500 | 2.7012 | 1.0 |
| 2.4301 | 3.6 | 2000 | 1.9785 | 1.3025 |
| 1.5285 | 4.5 | 2500 | 1.5775 | 1.4170 |
| 1.055 | 5.41 | 3000 | 1.5070 | 1.3753 |
| 0.8075 | 6.31 | 3500 | 1.3811 | 1.2509 |
| 0.6867 | 7.21 | 4000 | 1.2362 | 1.2007 |
| 0.566 | 8.11 | 4500 | 1.6537 | 1.2064 |
| 0.4967 | 9.01 | 5000 | 1.5271 | 1.1562 |
| 0.4337 | 9.91 | 5500 | 1.2359 | 1.1046 |
| 0.3941 | 10.81 | 6000 | 1.5255 | 1.1237 |
| 0.3612 | 11.71 | 6500 | 1.3686 | 1.0890 |
| 0.3237 | 12.61 | 7000 | 1.1992 | 1.0629 |
| 0.3085 | 13.51 | 7500 | 1.5883 | 1.0834 |
| 0.3003 | 14.41 | 8000 | 1.7352 | 1.0686 |
| 0.2859 | 15.32 | 8500 | 1.4790 | 0.9958 |
| 0.2495 | 16.22 | 9000 | 1.6757 | 1.0155 |
| 0.2329 | 17.12 | 9500 | 1.5789 | 1.0283 |
| 0.2241 | 18.02 | 10000 | 1.5147 | 0.9922 |
| 0.215 | 18.92 | 10500 | 1.4684 | 0.9965 |
| 0.202 | 19.82 | 11000 | 1.5099 | 0.9760 |
| 0.1942 | 20.72 | 11500 | 1.8195 | 0.9837 |
| 0.1627 | 21.62 | 12000 | 1.8089 | 1.0021 |
| 0.1782 | 22.52 | 12500 | 1.6944 | 0.9710 |
| 0.1566 | 23.42 | 13000 | 1.5881 | 0.9682 |
| 0.1471 | 24.32 | 13500 | 1.6741 | 0.9654 |
| 0.1355 | 25.23 | 14000 | 1.6183 | 0.9576 |
| 0.1253 | 26.13 | 14500 | 1.5730 | 0.9696 |
| 0.1245 | 27.03 | 15000 | 1.6876 | 0.9689 |
| 0.1258 | 27.93 | 15500 | 1.7535 | 0.9802 |
| 0.1217 | 28.83 | 16000 | 1.7710 | 0.9661 |
| 0.1074 | 29.73 | 16500 | 1.8002 | 0.9717 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2
