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--- |
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license: apache-2.0 |
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language: |
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- gn |
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tags: |
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- generated_from_trainer |
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- mozilla-foundation/common_voice_8_0 |
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- robust-speech-event |
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- hf-asr-leaderboard |
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datasets: |
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- common_voice |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: wav2vec2-base-gn-demo |
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results: [] |
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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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# wav2vec2-base-gn-demo |
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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: 0.7426 |
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- Wer: 0.7256 |
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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: 2e-05 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 60 |
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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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| No log | 4.0 | 100 | 0.7045 | 0.7409 | |
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| No log | 8.0 | 200 | 0.7200 | 0.75 | |
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| No log | 12.0 | 300 | 0.7400 | 0.7439 | |
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| No log | 16.0 | 400 | 0.7677 | 0.7515 | |
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| 0.0846 | 20.0 | 500 | 0.7765 | 0.7271 | |
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| 0.0846 | 24.0 | 600 | 0.7821 | 0.7287 | |
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| 0.0846 | 28.0 | 700 | 0.7671 | 0.7180 | |
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| 0.0846 | 32.0 | 800 | 0.7594 | 0.7180 | |
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| 0.0846 | 36.0 | 900 | 0.7500 | 0.7165 | |
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| 0.0713 | 40.0 | 1000 | 0.7351 | 0.7287 | |
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| 0.0713 | 44.0 | 1100 | 0.7361 | 0.7241 | |
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| 0.0713 | 48.0 | 1200 | 0.7389 | 0.7378 | |
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| 0.0713 | 52.0 | 1300 | 0.7424 | 0.7210 | |
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| 0.0713 | 56.0 | 1400 | 0.7425 | 0.7256 | |
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| 0.0669 | 60.0 | 1500 | 0.7426 | 0.7256 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.10.3 |
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