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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: ASR4-for-40-epochs |
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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: 0.26843348202571504 |
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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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# ASR4-for-40-epochs |
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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: 0.4791 |
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- Wer: 0.2684 |
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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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| 5.1111 | 0.92 | 100 | 0.7687 | 0.4387 | |
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| 1.1201 | 1.83 | 200 | 0.6388 | 0.3767 | |
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| 0.9734 | 2.75 | 300 | 0.6319 | 0.3658 | |
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| 0.9297 | 3.67 | 400 | 0.5740 | 0.3373 | |
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| 0.9142 | 4.59 | 500 | 0.5591 | 0.3268 | |
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| 0.8462 | 5.5 | 600 | 0.5627 | 0.3227 | |
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| 0.8366 | 6.42 | 700 | 0.5491 | 0.3158 | |
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| 0.8272 | 7.34 | 800 | 0.5398 | 0.3243 | |
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| 0.8137 | 8.26 | 900 | 0.5363 | 0.3113 | |
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| 0.7643 | 9.17 | 1000 | 0.5528 | 0.3117 | |
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| 0.7738 | 10.09 | 1100 | 0.5194 | 0.3285 | |
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| 0.7622 | 11.01 | 1200 | 0.5348 | 0.3043 | |
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| 0.707 | 11.93 | 1300 | 0.5179 | 0.2909 | |
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| 0.7242 | 12.84 | 1400 | 0.5153 | 0.3138 | |
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| 0.7093 | 13.76 | 1500 | 0.5116 | 0.2951 | |
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| 0.673 | 14.68 | 1600 | 0.5002 | 0.2941 | |
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| 0.6877 | 15.6 | 1700 | 0.4958 | 0.3050 | |
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| 0.6665 | 16.51 | 1800 | 0.5032 | 0.2865 | |
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| 0.6507 | 17.43 | 1900 | 0.4871 | 0.2809 | |
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| 0.6308 | 18.35 | 2000 | 0.4953 | 0.2947 | |
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| 0.6507 | 19.27 | 2100 | 0.4998 | 0.2837 | |
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| 0.6027 | 20.18 | 2200 | 0.4963 | 0.2868 | |
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| 0.623 | 21.1 | 2300 | 0.4955 | 0.2953 | |
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| 0.6047 | 22.02 | 2400 | 0.5034 | 0.2852 | |
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| 0.5825 | 22.94 | 2500 | 0.4781 | 0.2795 | |
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| 0.585 | 23.85 | 2600 | 0.4851 | 0.2843 | |
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| 0.5838 | 24.77 | 2700 | 0.4957 | 0.2742 | |
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| 0.5718 | 25.69 | 2800 | 0.4885 | 0.2810 | |
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| 0.5646 | 26.61 | 2900 | 0.4778 | 0.2724 | |
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| 0.5476 | 27.52 | 3000 | 0.4914 | 0.2751 | |
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| 0.5333 | 28.44 | 3100 | 0.4879 | 0.2788 | |
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| 0.5533 | 29.36 | 3200 | 0.4820 | 0.2726 | |
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| 0.5321 | 30.28 | 3300 | 0.4816 | 0.2686 | |
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| 0.5161 | 31.19 | 3400 | 0.4865 | 0.2812 | |
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| 0.5326 | 32.11 | 3500 | 0.4818 | 0.2704 | |
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| 0.5188 | 33.03 | 3600 | 0.4816 | 0.2669 | |
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| 0.506 | 33.94 | 3700 | 0.4804 | 0.2755 | |
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| 0.5122 | 34.86 | 3800 | 0.4803 | 0.2667 | |
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| 0.506 | 35.78 | 3900 | 0.4785 | 0.2708 | |
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| 0.5064 | 36.7 | 4000 | 0.4755 | 0.2730 | |
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| 0.4997 | 37.61 | 4100 | 0.4804 | 0.2708 | |
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| 0.4904 | 38.53 | 4200 | 0.4772 | 0.2678 | |
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| 0.4774 | 39.45 | 4300 | 0.4791 | 0.2684 | |
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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 2.16.1 |
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- Tokenizers 0.15.0 |
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