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wav2vec2-xlsr-53-espeak-cv-ft-sah-ntsema-colab
This model is a fine-tuned version of facebook/wav2vec2-xlsr-53-espeak-cv-ft on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2143
- Wer: 0.2247
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
2.7431 | 5.71 | 400 | 0.2879 | 0.4054 |
0.1876 | 11.42 | 800 | 0.2349 | 0.3023 |
0.0986 | 17.14 | 1200 | 0.2248 | 0.2701 |
0.0737 | 22.85 | 1600 | 0.2242 | 0.2428 |
0.0546 | 28.57 | 2000 | 0.2143 | 0.2247 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.14.0.dev20221105+cu116
- Datasets 2.6.1
- Tokenizers 0.13.1