<!-- 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. -->
wav2vec2-2
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9253
- Wer: 0.8133
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: 1e-05
- 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: 400
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
8.4469 | 0.34 | 200 | 3.7440 | 1.0 |
3.1152 | 0.69 | 400 | 3.3755 | 1.0 |
2.9228 | 1.03 | 600 | 3.0427 | 1.0 |
2.8661 | 1.38 | 800 | 2.9406 | 1.0 |
2.8402 | 1.72 | 1000 | 2.9034 | 1.0 |
2.8301 | 2.07 | 1200 | 2.8850 | 1.0 |
2.8088 | 2.41 | 1400 | 2.8479 | 1.0 |
2.6892 | 2.75 | 1600 | 2.5800 | 1.0 |
2.3249 | 3.1 | 1800 | 2.1310 | 1.0 |
1.9687 | 3.44 | 2000 | 1.7652 | 0.9982 |
1.7338 | 3.79 | 2200 | 1.5430 | 0.9974 |
1.5698 | 4.13 | 2400 | 1.3927 | 0.9985 |
1.4475 | 4.48 | 2600 | 1.3186 | 0.9911 |
1.3764 | 4.82 | 2800 | 1.2406 | 0.9647 |
1.3022 | 5.16 | 3000 | 1.1954 | 0.9358 |
1.2409 | 5.51 | 3200 | 1.1450 | 0.8990 |
1.1989 | 5.85 | 3400 | 1.1107 | 0.8794 |
1.1478 | 6.2 | 3600 | 1.0839 | 0.8667 |
1.106 | 6.54 | 3800 | 1.0507 | 0.8573 |
1.0792 | 6.88 | 4000 | 1.0179 | 0.8463 |
1.0636 | 7.23 | 4200 | 0.9974 | 0.8355 |
1.0224 | 7.57 | 4400 | 0.9757 | 0.8343 |
1.0166 | 7.92 | 4600 | 0.9641 | 0.8261 |
0.9925 | 8.26 | 4800 | 0.9553 | 0.8183 |
0.9934 | 8.61 | 5000 | 0.9466 | 0.8199 |
0.9741 | 8.95 | 5200 | 0.9353 | 0.8172 |
0.9613 | 9.29 | 5400 | 0.9331 | 0.8133 |
0.9714 | 9.64 | 5600 | 0.9272 | 0.8144 |
0.9593 | 9.98 | 5800 | 0.9253 | 0.8133 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1