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--- |
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language: |
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- rm-vallader |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_7_0 |
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- generated_from_trainer |
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- rm-vallader |
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- robust-speech-event |
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- model_for_talk |
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- hf-asr-leaderboard |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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model-index: |
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- name: XLS-R-300M - Romansh Vallader |
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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 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: rm-vallader |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 31.689 |
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- name: Test CER |
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type: cer |
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value: 7.202 |
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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-large-xls-r-300m-romansh-vallader |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - RM-VALLADER dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3155 |
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- Wer: 0.3162 |
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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: 7e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 1 |
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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: 100.0 |
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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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| 2.9556 | 15.62 | 500 | 2.9300 | 1.0 | |
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| 1.7874 | 31.25 | 1000 | 0.7566 | 0.6509 | |
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| 1.0131 | 46.88 | 1500 | 0.3671 | 0.3828 | |
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| 0.8439 | 62.5 | 2000 | 0.3350 | 0.3416 | |
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| 0.7502 | 78.12 | 2500 | 0.3155 | 0.3296 | |
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| 0.7093 | 93.75 | 3000 | 0.3182 | 0.3186 | |
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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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