wavlm-base
This model is a fine-tuned version of microsoft/wavlm-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3307
- Accuracy: 0.8974
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: 8
- eval_batch_size: 2
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.3744 | 1.0 | 793 | 0.3307 | 0.8974 |
0.3699 | 2.0 | 1586 | 0.3342 | 0.8974 |
0.2898 | 3.0 | 2379 | 0.3341 | 0.8974 |
0.3126 | 4.0 | 3173 | 0.3363 | 0.8974 |
0.3753 | 5.0 | 3966 | 0.3309 | 0.8974 |
0.3617 | 6.0 | 4759 | 0.3325 | 0.8974 |
0.3453 | 7.0 | 5552 | 0.3315 | 0.8974 |
0.3337 | 8.0 | 6346 | 0.3364 | 0.8974 |
0.2829 | 9.0 | 7139 | 0.3327 | 0.8974 |
0.3189 | 10.0 | 7930 | 0.3321 | 0.8974 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0.post302
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
microsoft/wavlm-base