wav2vec2-base-timit-demo-colab
This model is a fine-tuned version of facebook/wav2vec2-base on the timit_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.4243
- Wer: 0.2830
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: 32
- 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 |
---|---|---|---|---|
3.5112 | 3.45 | 500 | 1.1699 | 0.8236 |
0.5349 | 6.9 | 1000 | 0.3911 | 0.3609 |
0.1875 | 10.34 | 1500 | 0.3993 | 0.3170 |
0.1113 | 13.79 | 2000 | 0.3870 | 0.3046 |
0.0778 | 17.24 | 2500 | 0.4056 | 0.2963 |
0.0561 | 20.69 | 3000 | 0.3781 | 0.2918 |
0.0461 | 24.14 | 3500 | 0.4186 | 0.2857 |
0.0375 | 27.59 | 4000 | 0.4243 | 0.2830 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0
- Datasets 2.4.0
- Tokenizers 0.12.1
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This model can be loaded on the Inference API on-demand.