wav2vec2-base-mn-pretrain-42h-mn-silence-speech-commands
This model is a fine-tuned version of bayartsogt/wav2vec2-base-mn-pretrain-42h on the Mongolian Speech Commands dataset. It achieves the following results on the evaluation set:
- Loss: 0.0562
- Mn Acc: 0.9830
- Mn F1: 0.9832
- Silence Acc: 1.0
- Silence F1: 1.0
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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Mn Acc | Mn F1 | Silence Acc | Silence F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.4 | 8 | 2.0276 | 0.0455 | 0.0239 | 1.0 | 1.0 |
| 2.3615 | 0.8 | 16 | 1.1112 | 0.0057 | 0.0108 | 1.0 | 1.0 |
| 2.0154 | 1.2 | 24 | 0.6836 | 0.6307 | 0.5627 | 0.9975 | 0.9988 |
| 1.5733 | 1.6 | 32 | 0.4493 | 0.7898 | 0.7652 | 0.9975 | 0.9988 |
| 1.1148 | 2.0 | 40 | 0.3264 | 0.8409 | 0.8202 | 1.0 | 1.0 |
| 1.1148 | 2.4 | 48 | 0.2490 | 0.8864 | 0.8768 | 1.0 | 1.0 |
| 0.7937 | 2.8 | 56 | 0.1739 | 0.9545 | 0.9540 | 1.0 | 1.0 |
| 0.586 | 3.2 | 64 | 0.1425 | 0.9659 | 0.9664 | 1.0 | 1.0 |
| 0.4445 | 3.6 | 72 | 0.1137 | 0.9659 | 0.9659 | 1.0 | 1.0 |
| 0.3892 | 4.0 | 80 | 0.0942 | 0.9773 | 0.9772 | 1.0 | 1.0 |
| 0.3892 | 4.4 | 88 | 0.0914 | 0.9716 | 0.9717 | 1.0 | 1.0 |
| 0.3341 | 4.8 | 96 | 0.0748 | 0.9773 | 0.9775 | 1.0 | 1.0 |
| 0.2863 | 5.2 | 104 | 0.0670 | 0.9886 | 0.9886 | 1.0 | 1.0 |
| 0.2622 | 5.6 | 112 | 0.0697 | 0.9830 | 0.9832 | 1.0 | 1.0 |
| 0.2222 | 6.0 | 120 | 0.0638 | 0.9830 | 0.9832 | 1.0 | 1.0 |
| 0.2222 | 6.4 | 128 | 0.0580 | 0.9886 | 0.9886 | 1.0 | 1.0 |
| 0.213 | 6.8 | 136 | 0.0575 | 0.9830 | 0.9832 | 1.0 | 1.0 |
| 0.2082 | 7.2 | 144 | 0.0587 | 0.9830 | 0.9832 | 1.0 | 1.0 |
| 0.202 | 7.6 | 152 | 0.0582 | 0.9830 | 0.9832 | 1.0 | 1.0 |
| 0.1936 | 8.0 | 160 | 0.0562 | 0.9830 | 0.9832 | 1.0 | 1.0 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
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