wav2vec2-base
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4500
- Wer: 0.2132
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use adafactor and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 6000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1825 | 4.4267 | 500 | 0.2557 | 0.2045 |
0.1185 | 8.8533 | 1000 | 0.3017 | 0.2121 |
0.0937 | 13.2756 | 1500 | 0.3172 | 0.2039 |
0.0777 | 17.7022 | 2000 | 0.3681 | 0.2179 |
0.059 | 22.1244 | 2500 | 0.4151 | 0.2232 |
0.0673 | 26.5511 | 3000 | 0.4483 | 0.2138 |
0.0479 | 30.9778 | 3500 | 0.4478 | 0.2168 |
0.0463 | 35.4 | 4000 | 0.4102 | 0.2138 |
0.0436 | 39.8267 | 4500 | 0.4533 | 0.2109 |
0.0355 | 44.2489 | 5000 | 0.4166 | 0.2150 |
0.0242 | 48.6756 | 5500 | 0.4591 | 0.2156 |
0.0227 | 53.0978 | 6000 | 0.4500 | 0.2132 |
Framework versions
- Transformers 4.55.1
- Pytorch 2.8.0+cu129
- Datasets 3.6.0
- Tokenizers 0.21.4
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