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wav2vec2-large-xlsr-53-english-pronunciation-evaluation-aod-cut
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4268
- Accuracy: 0.6619
- F1: 0.6587
- Precision: 0.6571
- Recall: 0.6619
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.8845 | 1.0 | 308 | 0.8101 | 0.6457 | 0.5619 | 0.6263 | 0.6457 |
0.6667 | 2.0 | 616 | 0.8533 | 0.6209 | 0.6229 | 0.6477 | 0.6209 |
0.5061 | 3.0 | 924 | 0.9222 | 0.6534 | 0.6394 | 0.6375 | 0.6534 |
0.375 | 4.0 | 1232 | 1.2778 | 0.6611 | 0.6575 | 0.6570 | 0.6611 |
0.0501 | 5.0 | 1540 | 1.4268 | 0.6619 | 0.6587 | 0.6571 | 0.6619 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3