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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_11_0
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metrics:
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- wer
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model-index:
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- name: wav2vec2-large-xlsr-53-Bangla
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice_11_0
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type: common_voice_11_0
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config: bn
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split: train+validation
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args: bn
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metrics:
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- name: Wer
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type: wer
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value: 0.5442110214000156
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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-Bangla
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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 common_voice_11_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6125
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- Wer: 0.5442
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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: 0.0004
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- train_batch_size: 16
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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: 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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 4.6881 | 2.28 | 600 | 1.0325 | 0.9634 |
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| 0.8087 | 4.56 | 1200 | 0.6090 | 0.7430 |
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| 0.5089 | 6.84 | 1800 | 0.5156 | 0.6615 |
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| 0.3864 | 9.13 | 2400 | 0.5287 | 0.6676 |
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| 0.3064 | 11.41 | 3000 | 0.5411 | 0.6278 |
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| 0.2535 | 13.69 | 3600 | 0.5206 | 0.6149 |
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| 0.216 | 15.97 | 4200 | 0.5596 | 0.6120 |
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| 0.1852 | 18.25 | 4800 | 0.5658 | 0.5821 |
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| 0.1653 | 20.53 | 5400 | 0.5938 | 0.5521 |
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| 0.1499 | 22.81 | 6000 | 0.5825 | 0.5645 |
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| 0.1323 | 25.09 | 6600 | 0.6151 | 0.5593 |
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| 0.122 | 27.38 | 7200 | 0.6046 | 0.5556 |
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| 0.1118 | 29.66 | 7800 | 0.6125 | 0.5442 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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