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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: OpenSLR54 |
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type: kiranpantha/OpenSLR54-Balanced-Nepali |
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config: default |
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split: test |
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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: 0.4301989457575242 |
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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 OpenSLR54 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4052 |
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- Wer: 0.4302 |
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- Cer: 0.1029 |
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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: 5e-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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| 0.7515 | 0.15 | 300 | 0.4814 | 0.4911 | 0.1183 | |
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| 0.6554 | 0.3 | 600 | 0.5699 | 0.5382 | 0.1385 | |
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| 0.6723 | 0.45 | 900 | 0.5463 | 0.5401 | 0.1395 | |
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| 0.6635 | 0.6 | 1200 | 0.5244 | 0.5043 | 0.1250 | |
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| 0.6132 | 0.75 | 1500 | 0.4725 | 0.4831 | 0.1184 | |
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| 0.5786 | 0.9 | 1800 | 0.4620 | 0.4702 | 0.1147 | |
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| 0.5639 | 1.05 | 2100 | 0.4810 | 0.4668 | 0.1140 | |
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| 0.4863 | 1.2 | 2400 | 0.4639 | 0.4766 | 0.1151 | |
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| 0.4784 | 1.35 | 2700 | 0.4527 | 0.4611 | 0.1108 | |
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| 0.456 | 1.5 | 3000 | 0.4229 | 0.4458 | 0.1089 | |
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| 0.4613 | 1.65 | 3300 | 0.4460 | 0.4478 | 0.1095 | |
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| 0.4506 | 1.8 | 3600 | 0.4166 | 0.4413 | 0.1047 | |
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| 0.4369 | 1.95 | 3900 | 0.4052 | 0.4302 | 0.1029 | |
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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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