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--- |
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license: mit |
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base_model: facebook/w2v-bert-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_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-czech-colab-cv16 |
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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_16_0 |
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type: common_voice_16_0 |
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config: cs |
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split: test |
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args: cs |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.05733702722973076 |
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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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# w2v-bert-2.0-czech-colab-cv16 |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1023 |
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- Wer: 0.0573 |
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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: 64 |
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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: 500 |
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- num_epochs: 10 |
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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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| 1.5297 | 0.66 | 300 | 0.1448 | 0.1299 | |
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| 0.0886 | 1.32 | 600 | 0.1353 | 0.1051 | |
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| 0.0717 | 1.98 | 900 | 0.1157 | 0.0861 | |
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| 0.0463 | 2.64 | 1200 | 0.0994 | 0.0759 | |
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| 0.0404 | 3.3 | 1500 | 0.1054 | 0.0724 | |
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| 0.0314 | 3.96 | 1800 | 0.0915 | 0.0694 | |
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| 0.0227 | 4.63 | 2100 | 0.0926 | 0.0664 | |
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| 0.0205 | 5.29 | 2400 | 0.0992 | 0.0652 | |
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| 0.0161 | 5.95 | 2700 | 0.0932 | 0.0654 | |
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| 0.0124 | 6.61 | 3000 | 0.0902 | 0.0629 | |
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| 0.0097 | 7.27 | 3300 | 0.0970 | 0.0612 | |
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| 0.0081 | 7.93 | 3600 | 0.0946 | 0.0602 | |
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| 0.0054 | 8.59 | 3900 | 0.0962 | 0.0588 | |
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| 0.0048 | 9.25 | 4200 | 0.1029 | 0.0579 | |
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| 0.0034 | 9.91 | 4500 | 0.1023 | 0.0573 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.1 |
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