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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: facebook/w2v-bert-2.0 |
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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: 0.2604166666666667 |
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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 [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the OpenSLR54 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2182 |
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- Wer: 0.2604 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 4.4889 | 0.1800 | 300 | 0.8423 | 0.8076 | |
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| 0.7028 | 0.3599 | 600 | 0.6309 | 0.5951 | |
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| 0.5787 | 0.5399 | 900 | 0.5455 | 0.5167 | |
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| 0.476 | 0.7199 | 1200 | 0.4670 | 0.5109 | |
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| 0.4094 | 0.8998 | 1500 | 0.4415 | 0.4382 | |
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| 0.3345 | 1.0798 | 1800 | 0.3395 | 0.3951 | |
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| 0.2545 | 1.2597 | 2100 | 0.3266 | 0.3609 | |
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| 0.2444 | 1.4397 | 2400 | 0.2814 | 0.3204 | |
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| 0.2214 | 1.6197 | 2700 | 0.2593 | 0.2947 | |
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| 0.1846 | 1.7996 | 3000 | 0.2256 | 0.2685 | |
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| 0.1783 | 1.9796 | 3300 | 0.2182 | 0.2604 | |
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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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