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README.md
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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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datasets:
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- common_voice
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model-index:
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- name: wav2vec2-large-xls-r-300m-sakha
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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-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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