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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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- common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: firstcolab3 |
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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_11_0 |
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type: common_voice_11_0 |
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config: th |
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split: train+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: 0.6226224783861671 |
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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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# firstcolab3 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_11_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2756 |
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- Wer: 0.6226 |
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- Cer: 0.0535 |
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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: 500 |
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- num_epochs: 20 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 7.187 | 0.75 | 1000 | 3.7705 | 1.0 | 1.0 | |
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| 2.0277 | 1.5 | 2000 | 0.6139 | 0.9202 | 0.1545 | |
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| 0.8368 | 2.24 | 3000 | 0.4351 | 0.8589 | 0.1147 | |
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| 0.6772 | 2.99 | 4000 | 0.3762 | 0.8200 | 0.0990 | |
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| 0.5702 | 3.74 | 5000 | 0.3434 | 0.7889 | 0.0891 | |
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| 0.5205 | 4.49 | 6000 | 0.3427 | 0.7726 | 0.0855 | |
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| 0.4773 | 5.24 | 7000 | 0.3073 | 0.7408 | 0.0767 | |
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| 0.4389 | 5.98 | 8000 | 0.2969 | 0.7421 | 0.0759 | |
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| 0.4069 | 6.73 | 9000 | 0.2884 | 0.7134 | 0.0711 | |
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| 0.3858 | 7.48 | 10000 | 0.2952 | 0.7066 | 0.0699 | |
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| 0.36 | 8.23 | 11000 | 0.2846 | 0.6902 | 0.0662 | |
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| 0.3517 | 8.98 | 12000 | 0.2729 | 0.6756 | 0.0638 | |
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| 0.3265 | 9.72 | 13000 | 0.2844 | 0.6756 | 0.0645 | |
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| 0.3127 | 10.47 | 14000 | 0.2769 | 0.6803 | 0.0640 | |
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| 0.3016 | 11.22 | 15000 | 0.2772 | 0.6566 | 0.0618 | |
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| 0.2855 | 11.97 | 16000 | 0.2791 | 0.6540 | 0.0598 | |
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| 0.2699 | 12.72 | 17000 | 0.2714 | 0.6455 | 0.0589 | |
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| 0.264 | 13.46 | 18000 | 0.2782 | 0.6472 | 0.0588 | |
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| 0.2518 | 14.21 | 19000 | 0.2693 | 0.6398 | 0.0578 | |
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| 0.2498 | 14.96 | 20000 | 0.2761 | 0.6300 | 0.0561 | |
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| 0.2426 | 15.71 | 21000 | 0.2796 | 0.6366 | 0.0561 | |
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| 0.2271 | 16.45 | 22000 | 0.2804 | 0.6336 | 0.0554 | |
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| 0.2271 | 17.2 | 23000 | 0.2758 | 0.6347 | 0.0552 | |
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| 0.22 | 17.95 | 24000 | 0.2785 | 0.6279 | 0.0544 | |
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| 0.2143 | 18.7 | 25000 | 0.2783 | 0.6246 | 0.0538 | |
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| 0.2134 | 19.45 | 26000 | 0.2756 | 0.6226 | 0.0535 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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