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--- |
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license: cc-by-sa-4.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-detect-toxic-th |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice |
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type: common_voice |
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config: th |
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split: validation |
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args: th |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.4557774607703281 |
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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-detect-toxic-th |
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This model is a fine-tuned version of [airesearch/wav2vec2-large-xlsr-53-th](https://huggingface.co/airesearch/wav2vec2-large-xlsr-53-th) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0926 |
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- Wer: 0.4558 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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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_steps: 30 |
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- num_epochs: 35 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 5.4829 | 3.23 | 100 | 3.4277 | 1.0 | |
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| 3.301 | 6.45 | 200 | 3.2260 | 1.0 | |
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| 2.3 | 9.68 | 300 | 1.2590 | 0.5292 | |
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| 1.1601 | 12.9 | 400 | 1.0578 | 0.5892 | |
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| 0.9381 | 16.13 | 500 | 1.0390 | 0.4957 | |
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| 0.8211 | 19.35 | 600 | 1.0411 | 0.4679 | |
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| 0.7227 | 22.58 | 700 | 1.0614 | 0.4558 | |
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| 0.6805 | 25.81 | 800 | 1.0750 | 0.4579 | |
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| 0.6389 | 29.03 | 900 | 1.0678 | 0.4629 | |
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| 0.6045 | 32.26 | 1000 | 1.0926 | 0.4558 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 1.16.1 |
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- Tokenizers 0.13.3 |
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