wav2vec2-base-ks-linear_lrX10
This model is a fine-tuned version of facebook/wav2vec2-base on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 1.0471
- Accuracy: 0.6686
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: 256
- eval_batch_size: 256
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6226 | 1.0 | 50 | 1.7588 | 0.6209 |
| 1.382 | 2.0 | 100 | 1.5696 | 0.6209 |
| 1.2373 | 3.0 | 150 | 1.3818 | 0.6212 |
| 1.1019 | 4.0 | 200 | 1.2577 | 0.6228 |
| 0.9831 | 5.0 | 250 | 1.1826 | 0.6331 |
| 0.9241 | 6.0 | 300 | 1.1200 | 0.6481 |
| 0.8695 | 7.0 | 350 | 1.0821 | 0.6581 |
| 0.8529 | 8.0 | 400 | 1.0632 | 0.6652 |
| 0.8385 | 9.0 | 450 | 1.0494 | 0.6677 |
| 0.8162 | 10.0 | 500 | 1.0471 | 0.6686 |
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.11.0+cu115
- Datasets 2.4.0
- Tokenizers 0.12.1
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