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--- |
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license: apache-2.0 |
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language: |
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- es |
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tags: |
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- generated_from_trainer |
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- robust-speech-event |
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- common_voice_8_0 |
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- mozilla-foundation/common_voice_8_0 |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: wave2vec-xls-r-300m-es |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: mozilla-foundation/common_voice_8_0 es |
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type: mozilla-foundation/common_voice_8_0 |
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args: es |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 14.38 |
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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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# xls-r-300m-es with n-gram(5) |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss (Test): 0.1900 |
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- Wer (Test): 0.1438 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 4 |
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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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| 3.6747 | 0.3 | 400 | 0.6535 | 0.5926 | |
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| 0.4439 | 0.6 | 800 | 0.3753 | 0.3193 | |
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| 0.3291 | 0.9 | 1200 | 0.3267 | 0.2721 | |
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| 0.2644 | 1.2 | 1600 | 0.2816 | 0.2311 | |
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| 0.24 | 1.5 | 2000 | 0.2647 | 0.2179 | |
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| 0.2265 | 1.79 | 2400 | 0.2406 | 0.2048 | |
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| 0.1994 | 2.09 | 2800 | 0.2357 | 0.1869 | |
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| 0.1613 | 2.39 | 3200 | 0.2242 | 0.1821 | |
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| 0.1546 | 2.69 | 3600 | 0.2123 | 0.1707 | |
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| 0.1441 | 2.99 | 4000 | 0.2067 | 0.1619 | |
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| 0.1138 | 3.29 | 4400 | 0.2044 | 0.1519 | |
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| 0.1072 | 3.59 | 4800 | 0.1917 | 0.1457 | |
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| 0.0992 | 3.89 | 5200 | 0.1900 | 0.1438 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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