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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-Version1 |
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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: 0.5457385531582544 |
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name: Wer |
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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-Version1 |
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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: 0.7287 |
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- Wer: 0.5457 |
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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: 3e-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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- 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: 70 |
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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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| 3.6017 | 6.7568 | 500 | 3.5280 | 1.0 | |
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| 3.3879 | 13.5135 | 1000 | 3.3755 | 1.0 | |
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| 3.3566 | 20.2703 | 1500 | 3.3544 | 1.0 | |
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| 3.3133 | 27.0270 | 2000 | 3.2753 | 1.0 | |
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| 2.216 | 33.7838 | 2500 | 1.8757 | 0.9159 | |
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| 1.2972 | 40.5405 | 3000 | 1.0386 | 0.6969 | |
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| 1.0939 | 47.2973 | 3500 | 0.8590 | 0.6190 | |
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| 1.0188 | 54.0541 | 4000 | 0.7791 | 0.5797 | |
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| 0.9468 | 60.8108 | 4500 | 0.7461 | 0.5575 | |
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| 0.9806 | 67.5676 | 5000 | 0.7287 | 0.5457 | |
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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 |
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