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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/wav2vec2-base
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_17_0
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metrics:
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- wer
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model-index:
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- name: wav2vec2_common_voice17_finetuning
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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_17_0
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type: common_voice_17_0
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config: ro
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split: test
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args: ro
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metrics:
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- name: Wer
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type: wer
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value: 1.0
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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_voice17_finetuning
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4054
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- Wer: 1.0
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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: 32
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps: 5000
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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 | Wer |
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|:-------------:|:-------:|:----:|:---------------:|:------:|
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| 0.6577 | 3.5461 | 1000 | 0.4788 | 0.9997 |
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| 0.2893 | 7.0922 | 2000 | 0.4086 | 1.0 |
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| 0.1997 | 10.6383 | 3000 | 0.4135 | 0.9997 |
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| 0.156 | 14.1844 | 4000 | 0.4051 | 0.9992 |
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| 0.138 | 17.7305 | 5000 | 0.4054 | 1.0 |
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.4.1+cu124
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- Datasets 2.21.0
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- Tokenizers 0.21.0
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