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--- |
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language: |
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- vi |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ducha07/audio_HTV_thoisu |
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metrics: |
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- wer |
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model-index: |
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- name: ASR-test |
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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: HTV news |
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type: ducha07/audio_HTV_thoisu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.2882930019620667 |
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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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# ASR-test-1 |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the HTV news dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5663 |
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- Wer: 0.2883 |
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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: 0.001 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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: 100 |
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- num_epochs: 40 |
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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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| 4.772 | 0.92 | 100 | 0.8456 | 0.4411 | |
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| 1.1042 | 1.83 | 200 | 0.7041 | 0.4076 | |
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| 0.9814 | 2.75 | 300 | 0.7243 | 0.3782 | |
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| 0.9096 | 3.67 | 400 | 0.6771 | 0.3655 | |
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| 0.8823 | 4.59 | 500 | 0.6265 | 0.3627 | |
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| 0.8435 | 5.5 | 600 | 0.6200 | 0.3543 | |
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| 0.8157 | 6.42 | 700 | 0.6414 | 0.3417 | |
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| 0.822 | 7.34 | 800 | 0.5872 | 0.3431 | |
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| 0.7852 | 8.26 | 900 | 0.6012 | 0.3387 | |
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| 0.7533 | 9.17 | 1000 | 0.6023 | 0.3256 | |
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| 0.7609 | 10.09 | 1100 | 0.5837 | 0.3444 | |
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| 0.7568 | 11.01 | 1200 | 0.5791 | 0.3311 | |
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| 0.7091 | 11.93 | 1300 | 0.6227 | 0.3206 | |
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| 0.7098 | 12.84 | 1400 | 0.5766 | 0.3266 | |
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| 0.7006 | 13.76 | 1500 | 0.6084 | 0.3117 | |
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| 0.6673 | 14.68 | 1600 | 0.5857 | 0.3120 | |
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| 0.6832 | 15.6 | 1700 | 0.5754 | 0.3338 | |
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| 0.6646 | 16.51 | 1800 | 0.5963 | 0.3117 | |
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| 0.6524 | 17.43 | 1900 | 0.5816 | 0.3137 | |
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| 0.6385 | 18.35 | 2000 | 0.5691 | 0.3257 | |
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| 0.6433 | 19.27 | 2100 | 0.5929 | 0.3105 | |
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| 0.6129 | 20.18 | 2200 | 0.5709 | 0.3067 | |
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| 0.624 | 21.1 | 2300 | 0.5686 | 0.3168 | |
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| 0.6128 | 22.02 | 2400 | 0.5867 | 0.3080 | |
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| 0.584 | 22.94 | 2500 | 0.5680 | 0.3101 | |
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| 0.5956 | 23.85 | 2600 | 0.5611 | 0.3023 | |
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| 0.5825 | 24.77 | 2700 | 0.5821 | 0.2999 | |
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| 0.56 | 25.69 | 2800 | 0.5622 | 0.3012 | |
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| 0.56 | 26.61 | 2900 | 0.5590 | 0.3053 | |
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| 0.5523 | 27.52 | 3000 | 0.5758 | 0.2967 | |
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| 0.5335 | 28.44 | 3100 | 0.5649 | 0.3090 | |
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| 0.5686 | 29.36 | 3200 | 0.5703 | 0.2931 | |
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| 0.5488 | 30.28 | 3300 | 0.5709 | 0.2921 | |
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| 0.5249 | 31.19 | 3400 | 0.5646 | 0.2973 | |
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| 0.5278 | 32.11 | 3500 | 0.5628 | 0.2933 | |
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| 0.5252 | 33.03 | 3600 | 0.5663 | 0.2927 | |
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| 0.5092 | 33.94 | 3700 | 0.5618 | 0.2922 | |
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| 0.5099 | 34.86 | 3800 | 0.5616 | 0.2954 | |
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| 0.5031 | 35.78 | 3900 | 0.5670 | 0.2913 | |
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| 0.4959 | 36.7 | 4000 | 0.5679 | 0.2923 | |
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| 0.4936 | 37.61 | 4100 | 0.5675 | 0.2912 | |
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| 0.5012 | 38.53 | 4200 | 0.5661 | 0.2897 | |
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| 0.4819 | 39.45 | 4300 | 0.5663 | 0.2883 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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