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--- |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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datasets: |
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- fleurs |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- wer |
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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-Hindi-Version3 |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: fleurs |
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type: fleurs |
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config: hi_in |
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split: None |
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args: hi_in |
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metrics: |
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- type: wer |
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value: 0.282143903153373 |
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name: Wer |
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language: |
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- hi |
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pipeline_tag: automatic-speech-recognition |
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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-Hindi-Version3 |
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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 fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7311 |
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- Wer: 0.2821 |
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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: 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: 100 |
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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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| 3.362 | 6.7568 | 500 | 3.3795 | 1.0 | |
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| 0.5309 | 13.5135 | 1000 | 0.5572 | 0.4268 | |
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| 0.2342 | 20.2703 | 1500 | 0.5206 | 0.3341 | |
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| 0.1408 | 27.0270 | 2000 | 0.5516 | 0.3292 | |
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| 0.1126 | 33.7838 | 2500 | 0.6105 | 0.3199 | |
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| 0.0892 | 40.5405 | 3000 | 0.6489 | 0.3123 | |
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| 0.0721 | 47.2973 | 3500 | 0.6533 | 0.3067 | |
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| 0.0719 | 54.0541 | 4000 | 0.6898 | 0.3050 | |
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| 0.0592 | 60.8108 | 4500 | 0.7007 | 0.2990 | |
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| 0.0737 | 67.5676 | 5000 | 0.7106 | 0.2921 | |
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| 0.0399 | 74.3243 | 5500 | 0.7271 | 0.2916 | |
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| 0.0409 | 81.0811 | 6000 | 0.7298 | 0.2871 | |
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| 0.0322 | 87.8378 | 6500 | 0.7311 | 0.2835 | |
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| 0.0285 | 94.5946 | 7000 | 0.7311 | 0.2821 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
