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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_scotland
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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_scotland
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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: 0.2752
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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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| 4.7171 | 1.28 | 400 | 1.1618 |
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| 0.4391 | 2.56 | 800 | 0.2422 |
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| 0.2259 | 3.83 | 1200 | 0.2071 |
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| 0.1813 | 5.11 | 1600 | 0.2126 |
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| 0.1531 | 6.39 | 2000 | 0.2010 |
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| 0.1383 | 7.67 | 2400 | 0.2004 |
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| 0.13 | 8.95 | 2800 | 0.2069 |
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| 0.1193 | 10.22 | 3200 | 0.2081 |
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| 0.1124 | 11.5 | 3600 | 0.2051 |
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| 0.1023 | 12.78 | 4000 | 0.2175 |
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| 0.097 | 14.06 | 4400 | 0.2261 |
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| 0.0863 | 15.34 | 4800 | 0.2301 |
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| 0.0823 | 16.61 | 5200 | 0.2334 |
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| 0.079 | 17.89 | 5600 | 0.2252 |
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| 0.0743 | 19.17 | 6000 | 0.2393 |
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| 0.0696 | 20.45 | 6400 | 0.2481 |
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| 0.0644 | 21.73 | 6800 | 0.2416 |
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| 0.064 | 23.0 | 7200 | 0.2449 |
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| 0.0584 | 24.28 | 7600 | 0.2660 |
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| 0.0544 | 25.56 | 8000 | 0.2630 |
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| 0.0523 | 26.84 | 8400 | 0.2677 |
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| 0.0494 | 28.12 | 8800 | 0.2730 |
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| 0.0462 | 29.39 | 9200 | 0.2752 |
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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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