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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- bayartsogt/mongolian_speech_commands |
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model-index: |
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- name: wav2vec2-base-mn-pretrain-42h-mn-silence-speech-commands |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-base-mn-pretrain-42h-mn-silence-speech-commands |
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This model is a fine-tuned version of [bayartsogt/wav2vec2-base-mn-pretrain-42h](https://huggingface.co/bayartsogt/wav2vec2-base-mn-pretrain-42h) on the Mongolian Speech Commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0562 |
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- Mn Acc: 0.9830 |
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- Mn F1: 0.9832 |
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- Silence Acc: 1.0 |
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- Silence F1: 1.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mn Acc | Mn F1 | Silence Acc | Silence F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-----------:|:----------:| |
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| No log | 0.4 | 8 | 2.0276 | 0.0455 | 0.0239 | 1.0 | 1.0 | |
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| 2.3615 | 0.8 | 16 | 1.1112 | 0.0057 | 0.0108 | 1.0 | 1.0 | |
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| 2.0154 | 1.2 | 24 | 0.6836 | 0.6307 | 0.5627 | 0.9975 | 0.9988 | |
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| 1.5733 | 1.6 | 32 | 0.4493 | 0.7898 | 0.7652 | 0.9975 | 0.9988 | |
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| 1.1148 | 2.0 | 40 | 0.3264 | 0.8409 | 0.8202 | 1.0 | 1.0 | |
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| 1.1148 | 2.4 | 48 | 0.2490 | 0.8864 | 0.8768 | 1.0 | 1.0 | |
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| 0.7937 | 2.8 | 56 | 0.1739 | 0.9545 | 0.9540 | 1.0 | 1.0 | |
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| 0.586 | 3.2 | 64 | 0.1425 | 0.9659 | 0.9664 | 1.0 | 1.0 | |
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| 0.4445 | 3.6 | 72 | 0.1137 | 0.9659 | 0.9659 | 1.0 | 1.0 | |
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| 0.3892 | 4.0 | 80 | 0.0942 | 0.9773 | 0.9772 | 1.0 | 1.0 | |
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| 0.3892 | 4.4 | 88 | 0.0914 | 0.9716 | 0.9717 | 1.0 | 1.0 | |
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| 0.3341 | 4.8 | 96 | 0.0748 | 0.9773 | 0.9775 | 1.0 | 1.0 | |
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| 0.2863 | 5.2 | 104 | 0.0670 | 0.9886 | 0.9886 | 1.0 | 1.0 | |
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| 0.2622 | 5.6 | 112 | 0.0697 | 0.9830 | 0.9832 | 1.0 | 1.0 | |
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| 0.2222 | 6.0 | 120 | 0.0638 | 0.9830 | 0.9832 | 1.0 | 1.0 | |
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| 0.2222 | 6.4 | 128 | 0.0580 | 0.9886 | 0.9886 | 1.0 | 1.0 | |
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| 0.213 | 6.8 | 136 | 0.0575 | 0.9830 | 0.9832 | 1.0 | 1.0 | |
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| 0.2082 | 7.2 | 144 | 0.0587 | 0.9830 | 0.9832 | 1.0 | 1.0 | |
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| 0.202 | 7.6 | 152 | 0.0582 | 0.9830 | 0.9832 | 1.0 | 1.0 | |
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| 0.1936 | 8.0 | 160 | 0.0562 | 0.9830 | 0.9832 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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