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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xlsr-53-Marathi-large |
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results: [] |
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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-xlsr-53-Marathi-large |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3832 |
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- Wer: 0.2102 |
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- Cer: 0.0667 |
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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: 6 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 24 |
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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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- training_steps: 3000 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 6.4763 | 1.7647 | 300 | 3.3057 | 1.0 | 1.0 | |
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| 1.3413 | 3.5294 | 600 | 0.6503 | 0.4479 | 0.1574 | |
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| 0.4712 | 5.2941 | 900 | 0.4442 | 0.3447 | 0.1126 | |
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| 0.2772 | 7.0588 | 1200 | 0.4034 | 0.2922 | 0.0970 | |
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| 0.1741 | 8.8235 | 1500 | 0.3750 | 0.2518 | 0.0814 | |
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| 0.1213 | 10.5882 | 1800 | 0.3936 | 0.2435 | 0.0787 | |
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| 0.0889 | 12.3529 | 2100 | 0.3841 | 0.2271 | 0.0736 | |
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| 0.0718 | 14.1176 | 2400 | 0.3675 | 0.2116 | 0.0680 | |
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| 0.0546 | 15.8824 | 2700 | 0.3755 | 0.2134 | 0.0676 | |
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| 0.047 | 17.6471 | 3000 | 0.3832 | 0.2102 | 0.0667 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 1.18.3 |
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- Tokenizers 0.19.1 |
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