wav2vec2-large_phoneme-timit_english_timit-4k_001
This model is a fine-tuned version of facebook/wav2vec2-large on the timit dataset. It achieves the following results on the evaluation set:
- Loss: 0.4952
- Per: 0.1134
Model description
The wav2vec 2.0 large model is pre-trained on 960 hours of the LibriSpeech dataset.
- 24 Transformer blocks (Each block: 1024 dimensions & 16 attention heads)
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Per |
|---|---|---|---|---|
| 4.5458 | 3.46 | 1000 | 0.9087 | 0.2354 |
| 0.7877 | 6.92 | 2000 | 0.4441 | 0.1506 |
| 0.5125 | 10.38 | 3000 | 0.4241 | 0.1451 |
| 0.4485 | 13.84 | 4000 | 0.4244 | 0.1461 |
| 0.4193 | 17.3 | 5000 | 0.4618 | 0.1510 |
| 0.3899 | 20.76 | 6000 | 0.4700 | 0.1469 |
| 0.3244 | 24.22 | 7000 | 0.4496 | 0.1438 |
| 0.2717 | 27.68 | 8000 | 0.4988 | 0.1455 |
| 0.2222 | 31.14 | 9000 | 0.5182 | 0.1414 |
| 0.1872 | 34.6 | 10000 | 0.5320 | 0.1411 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.13.3
- Downloads last month
- 0
This model does not have enough activity to be deployed to Inference API (serverless) yet.
Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.