wav2vec2-base-ks-linear_lrX100
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: 0.6970
- Accuracy: 0.8001
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: 0.003
- 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 |
|---|---|---|---|---|
| 1.1789 | 1.0 | 50 | 1.3621 | 0.6225 |
| 0.636 | 2.0 | 100 | 0.9176 | 0.6912 |
| 0.5575 | 3.0 | 150 | 0.8543 | 0.7376 |
| 0.5289 | 4.0 | 200 | 0.6970 | 0.8001 |
| 0.4926 | 5.0 | 250 | 0.8232 | 0.7548 |
| 0.4831 | 6.0 | 300 | 0.7442 | 0.7755 |
| 0.4539 | 7.0 | 350 | 0.7484 | 0.7785 |
| 0.4816 | 8.0 | 400 | 0.7038 | 0.7982 |
| 0.4666 | 9.0 | 450 | 0.7277 | 0.7764 |
| 0.4417 | 10.0 | 500 | 0.7289 | 0.7870 |
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.11.0+cu115
- Datasets 2.4.0
- Tokenizers 0.12.1