results
This model is a fine-tuned version of airesearch/wav2vec2-large-xlsr-53-th on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7323
- Wer: 0.7679
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: 1
- 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_steps: 400
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
8.3585 | 0.25 | 200 | 3.7485 | 1.0 |
3.8093 | 0.5 | 400 | 3.8628 | 1.0 |
3.5329 | 0.75 | 600 | 3.2145 | 1.0338 |
2.863 | 1.0 | 800 | 2.3523 | 1.0338 |
2.5961 | 1.25 | 1000 | 2.2498 | 0.9430 |
2.2367 | 1.5 | 1200 | 1.8962 | 0.9367 |
2.3278 | 1.75 | 1400 | 1.7836 | 0.8819 |
2.3837 | 2.0 | 1600 | 1.7629 | 0.8734 |
1.8619 | 2.25 | 1800 | 1.6965 | 0.7996 |
1.7128 | 2.5 | 2000 | 1.6921 | 0.8460 |
1.8454 | 2.75 | 2200 | 1.6593 | 0.8249 |
2.0607 | 3.0 | 2400 | 1.5911 | 0.8376 |
1.4646 | 3.25 | 2600 | 1.8107 | 0.8186 |
1.607 | 3.5 | 2800 | 1.6033 | 0.7806 |
1.5235 | 3.75 | 3000 | 1.6470 | 0.7785 |
1.3815 | 4.0 | 3200 | 1.6569 | 0.7616 |
1.1566 | 4.25 | 3400 | 1.6391 | 0.8017 |
1.3227 | 4.5 | 3600 | 1.7540 | 0.7574 |
1.2177 | 4.75 | 3800 | 1.7102 | 0.7743 |
1.2427 | 5.0 | 4000 | 1.5678 | 0.7363 |
0.9828 | 5.25 | 4200 | 1.6312 | 0.7616 |
0.9598 | 5.5 | 4400 | 1.6054 | 0.7384 |
1.1113 | 5.75 | 4600 | 1.6230 | 0.7215 |
1.0259 | 6.0 | 4800 | 1.7928 | 0.7700 |
0.855 | 6.25 | 5000 | 1.6485 | 0.7616 |
0.8293 | 6.5 | 5200 | 1.6819 | 0.7806 |
0.924 | 6.75 | 5400 | 1.6014 | 0.7679 |
0.8574 | 7.0 | 5600 | 1.6276 | 0.7447 |
0.6518 | 7.25 | 5800 | 1.5983 | 0.7595 |
0.7592 | 7.5 | 6000 | 1.6340 | 0.7679 |
0.6812 | 7.75 | 6200 | 1.7337 | 0.7595 |
0.7568 | 8.0 | 6400 | 1.6422 | 0.7363 |
0.7599 | 8.25 | 6600 | 1.6896 | 0.7700 |
0.5626 | 8.5 | 6800 | 1.7042 | 0.7658 |
0.5976 | 8.75 | 7000 | 1.7000 | 0.7532 |
0.6649 | 9.0 | 7200 | 1.7071 | 0.7658 |
0.5831 | 9.25 | 7400 | 1.7440 | 0.7679 |
0.5708 | 9.5 | 7600 | 1.6950 | 0.7574 |
0.4576 | 9.75 | 7800 | 1.7286 | 0.7679 |
0.4547 | 10.0 | 8000 | 1.7323 | 0.7679 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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