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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_indian_only_rerun
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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_indian_only_rerun
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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: 1.2807
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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: 588
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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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| 4.6205 | 25.0 | 400 | 1.4584 |
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| 0.3427 | 50.0 | 800 | 1.8377 |
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| 0.1213 | 75.0 | 1200 | 1.6086 |
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| 0.0643 | 100.0 | 1600 | 1.5136 |
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| 0.0433 | 125.0 | 2000 | 1.4882 |
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| 0.0323 | 150.0 | 2400 | 1.2204 |
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| 0.0265 | 175.0 | 2800 | 1.3034 |
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| 0.0206 | 200.0 | 3200 | 1.2866 |
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| 0.0191 | 225.0 | 3600 | 1.2337 |
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| 0.0148 | 250.0 | 4000 | 1.1729 |
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| 0.0121 | 275.0 | 4400 | 1.2059 |
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| 0.0105 | 300.0 | 4800 | 1.1246 |
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| 0.01 | 325.0 | 5200 | 1.1397 |
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| 0.0098 | 350.0 | 5600 | 1.1684 |
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| 0.0073 | 375.0 | 6000 | 1.1030 |
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| 0.0061 | 400.0 | 6400 | 1.2077 |
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| 0.0049 | 425.0 | 6800 | 1.2653 |
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| 0.0044 | 450.0 | 7200 | 1.1587 |
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| 0.0037 | 475.0 | 7600 | 1.2283 |
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| 0.0033 | 500.0 | 8000 | 1.1897 |
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| 0.0026 | 525.0 | 8400 | 1.2633 |
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| 0.0023 | 550.0 | 8800 | 1.2571 |
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| 0.002 | 575.0 | 9200 | 1.2807 |
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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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