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--- |
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license: apache-2.0 |
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base_model: Strange18/wav2vec2-nepali-asr |
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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-nepali-asr |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/prashant-bista-18-thapathali-campus/Created%20Dataset%20ASR/runs/s8f6s4q9) |
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# wav2vec2-nepali-asr |
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This model is a fine-tuned version of [Strange18/wav2vec2-nepali-asr](https://huggingface.co/Strange18/wav2vec2-nepali-asr) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3957 |
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- Wer: 0.3705 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 50 |
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- num_epochs: 15 |
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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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| 0.7578 | 1.5464 | 75 | 0.5105 | 0.4879 | |
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| 0.6844 | 3.0928 | 150 | 0.4736 | 0.4575 | |
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| 0.6367 | 4.6392 | 225 | 0.4586 | 0.4291 | |
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| 0.5977 | 6.1856 | 300 | 0.4387 | 0.4170 | |
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| 0.5714 | 7.7320 | 375 | 0.4350 | 0.4170 | |
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| 0.5815 | 9.2784 | 450 | 0.4255 | 0.4109 | |
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| 0.5629 | 10.8247 | 525 | 0.4260 | 0.4049 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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