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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Marathi_ASR_using_xlsr_wav2vec |
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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_13_0 |
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type: common_voice_13_0 |
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config: mr |
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split: test |
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args: mr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.7180765086206896 |
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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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# Marathi_ASR_using_xlsr_wav2vec |
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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_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7582 |
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- Wer: 0.7181 |
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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: 1e-05 |
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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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- 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: 300 |
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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 | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| No log | 2.6667 | 200 | 0.7381 | 0.7263 | |
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| 0.336 | 5.3333 | 400 | 0.7472 | 0.7289 | |
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| 0.336 | 8.0 | 600 | 0.7452 | 0.7215 | |
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| 0.3237 | 10.6667 | 800 | 0.7449 | 0.7212 | |
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| 0.3237 | 13.3333 | 1000 | 0.7546 | 0.7192 | |
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| 0.3104 | 16.0 | 1200 | 0.7565 | 0.7210 | |
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| 0.3104 | 18.6667 | 1400 | 0.7550 | 0.7193 | |
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| 0.3089 | 21.3333 | 1600 | 0.7551 | 0.7186 | |
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| 0.3089 | 24.0 | 1800 | 0.7572 | 0.7185 | |
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| 0.2993 | 26.6667 | 2000 | 0.7571 | 0.7175 | |
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| 0.2993 | 29.3333 | 2200 | 0.7582 | 0.7181 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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