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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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- accuracy |
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model-index: |
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- name: asr-nepali |
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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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# asr-nepali |
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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: nan |
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- Wer: 1.0 |
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- Cer: 0.9965 |
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- Accuracy: 0.0035 |
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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: 180 |
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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 | Cer | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---:|:------:|:--------:| |
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| 451.545 | 1.46 | 100 | 43.3285 | 1.0 | 0.9684 | 0.0316 | |
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| 194.4567 | 2.92 | 200 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 4.38 | 300 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 5.84 | 400 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 7.3 | 500 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 8.76 | 600 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 10.22 | 700 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 11.68 | 800 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 13.14 | 900 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 14.6 | 1000 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 16.06 | 1100 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 17.52 | 1200 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 18.98 | 1300 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 20.44 | 1400 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 21.9 | 1500 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 23.36 | 1600 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 24.82 | 1700 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 26.28 | 1800 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 27.74 | 1900 | nan | 1.0 | 0.9965 | 0.0035 | |
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| 0.0 | 29.2 | 2000 | nan | 1.0 | 0.9965 | 0.0035 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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