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--- |
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language: |
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- sah |
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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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- sah |
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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 - Sakha |
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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: sah |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 44.196 |
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- name: Test CER |
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type: cer |
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value: 10.271 |
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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-sakha |
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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 - SAH dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4995 |
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- Wer: 0.4421 |
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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: 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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| 1.8597 | 8.47 | 500 | 0.7731 | 0.7211 | |
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| 1.2508 | 16.95 | 1000 | 0.5368 | 0.5989 | |
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| 1.1066 | 25.42 | 1500 | 0.5034 | 0.5533 | |
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| 1.0064 | 33.9 | 2000 | 0.4686 | 0.5114 | |
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| 0.9324 | 42.37 | 2500 | 0.4927 | 0.5056 | |
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| 0.876 | 50.85 | 3000 | 0.4734 | 0.4795 | |
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| 0.8082 | 59.32 | 3500 | 0.4748 | 0.4799 | |
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| 0.7604 | 67.8 | 4000 | 0.4949 | 0.4691 | |
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| 0.7241 | 76.27 | 4500 | 0.5090 | 0.4627 | |
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| 0.6739 | 84.75 | 5000 | 0.4967 | 0.4452 | |
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| 0.6447 | 93.22 | 5500 | 0.5071 | 0.4437 | |
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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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