wav2vec2-base-en-asr-timit
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: 0.4525
- Wer: 0.3510
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: 64
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.6253 | 3.17 | 200 | 3.0613 | 1.0 |
| 2.9038 | 6.35 | 400 | 2.7513 | 1.0 |
| 1.5048 | 9.52 | 600 | 0.6193 | 0.5702 |
| 0.4196 | 12.7 | 800 | 0.4788 | 0.4464 |
| 0.2203 | 15.87 | 1000 | 0.4743 | 0.4098 |
| 0.1439 | 19.05 | 1200 | 0.4420 | 0.3804 |
| 0.0963 | 22.22 | 1400 | 0.4587 | 0.3620 |
| 0.073 | 25.4 | 1600 | 0.4681 | 0.3588 |
| 0.0603 | 28.57 | 1800 | 0.4525 | 0.3510 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2
- Downloads last month
- 6
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.