wav2vec2-base-TPU-cv-fine-tune-2
This model is a fine-tuned version of jiobiala24/wav2vec2-base-TPU-cv-fine-tune on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 1.6051
- Wer: 0.5484
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.522 | 6.45 | 400 | 1.2550 | 0.5649 |
0.2874 | 12.9 | 800 | 1.4235 | 0.6054 |
0.152 | 19.35 | 1200 | 1.5743 | 0.5806 |
0.0857 | 25.8 | 1600 | 1.6051 | 0.5484 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
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