update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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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_common_voice_accents_us
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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_common_voice_accents_us
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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: 0.2722
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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: 48
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 384
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- total_eval_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: 30
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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 |
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|:-------------:|:-----:|:----:|:---------------:|
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| 4.549 | 1.28 | 400 | 0.8521 |
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| 0.4066 | 2.56 | 800 | 0.2407 |
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| 0.2262 | 3.83 | 1200 | 0.2070 |
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| 0.1828 | 5.11 | 1600 | 0.2134 |
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| 0.1565 | 6.39 | 2000 | 0.2060 |
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| 0.1448 | 7.67 | 2400 | 0.2100 |
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| 0.1333 | 8.95 | 2800 | 0.2036 |
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| 0.121 | 10.22 | 3200 | 0.2192 |
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| 0.1146 | 11.5 | 3600 | 0.2154 |
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| 0.1108 | 12.78 | 4000 | 0.2223 |
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| 0.1017 | 14.06 | 4400 | 0.2331 |
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| 0.094 | 15.34 | 4800 | 0.2257 |
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| 0.0896 | 16.61 | 5200 | 0.2229 |
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| 0.0825 | 17.89 | 5600 | 0.2229 |
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| 0.0777 | 19.17 | 6000 | 0.2417 |
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| 0.0719 | 20.45 | 6400 | 0.2433 |
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| 0.0659 | 21.73 | 6800 | 0.2447 |
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| 0.0651 | 23.0 | 7200 | 0.2446 |
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| 0.0587 | 24.28 | 7600 | 0.2542 |
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| 0.056 | 25.56 | 8000 | 0.2587 |
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| 0.0521 | 26.84 | 8400 | 0.2640 |
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| 0.0494 | 28.12 | 8800 | 0.2753 |
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| 0.0465 | 29.39 | 9200 | 0.2722 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.4
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- Tokenizers 0.11.6
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