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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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model-index:
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- name: wav2vec2-large-xlsr-53_toy_train_data_augmented
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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-xlsr-53_toy_train_data_augmented
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5016
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- Wer: 0.4656
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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: 0.0001
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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: 1000
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- num_epochs: 20
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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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| 3.418 | 1.05 | 250 | 3.4171 | 1.0 |
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| 3.0886 | 2.1 | 500 | 3.4681 | 1.0 |
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| 2.9422 | 3.15 | 750 | 2.6151 | 1.0 |
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| 1.3195 | 4.2 | 1000 | 0.8789 | 0.7739 |
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| 0.9154 | 5.25 | 1250 | 0.6364 | 0.6518 |
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| 0.6519 | 6.3 | 1500 | 0.5682 | 0.5949 |
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| 0.5622 | 7.35 | 1750 | 0.5273 | 0.5625 |
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| 0.4965 | 8.4 | 2000 | 0.4891 | 0.5283 |
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| 0.4283 | 9.45 | 2250 | 0.5018 | 0.5260 |
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| 0.4019 | 10.5 | 2500 | 0.5016 | 0.5006 |
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| 0.3585 | 11.55 | 2750 | 0.5047 | 0.5003 |
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| 0.3275 | 12.6 | 3000 | 0.5148 | 0.4866 |
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| 0.3427 | 13.65 | 3250 | 0.5035 | 0.4786 |
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| 0.3229 | 14.7 | 3500 | 0.4855 | 0.4768 |
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| 0.3332 | 15.75 | 3750 | 0.5040 | 0.4769 |
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| 0.2861 | 16.81 | 4000 | 0.5138 | 0.4669 |
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| 0.3029 | 17.86 | 4250 | 0.5133 | 0.4670 |
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| 0.2633 | 18.91 | 4500 | 0.5063 | 0.4637 |
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| 0.2621 | 19.96 | 4750 | 0.5016 | 0.4656 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.11.0+cu102
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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