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--- |
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library_name: transformers |
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language: |
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- ne |
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license: mit |
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base_model: kiranpantha/w2v-bert-2.0-nepali |
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tags: |
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- generated_from_trainer |
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datasets: |
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- kiranpantha/OpenSLR54-Balanced-Nepali |
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metrics: |
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- wer |
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model-index: |
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- name: Wave2Vec2-Bert2.0 - Kiran Pantha |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: kiranpantha/OpenSLR54-Balanced-Nepali |
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type: kiranpantha/OpenSLR54-Balanced-Nepali |
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args: 'config: ne, split: train,test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3611633875106929 |
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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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# Wave2Vec2-Bert2.0 - Kiran Pantha |
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This model is a fine-tuned version of [kiranpantha/w2v-bert-2.0-nepali](https://huggingface.co/kiranpantha/w2v-bert-2.0-nepali) on the kiranpantha/OpenSLR54-Balanced-Nepali dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3414 |
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- Wer: 0.3612 |
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- Cer: 0.0805 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 2 |
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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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| 0.4176 | 0.24 | 300 | 0.3260 | 0.3485 | 0.0772 | |
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| 0.4128 | 0.48 | 600 | 0.3514 | 0.3620 | 0.0810 | |
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| 0.4161 | 0.72 | 900 | 0.3460 | 0.3618 | 0.0810 | |
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| 0.3578 | 0.96 | 1200 | 0.3366 | 0.3528 | 0.0804 | |
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| 0.359 | 1.2 | 1500 | 0.3595 | 0.3577 | 0.0787 | |
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| 0.3371 | 1.44 | 1800 | 0.3446 | 0.3634 | 0.0808 | |
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| 0.3309 | 1.6800 | 2100 | 0.3399 | 0.3677 | 0.0818 | |
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| 0.3441 | 1.92 | 2400 | 0.3414 | 0.3612 | 0.0805 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.0+cu124 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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