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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: 0.25254629629629627 |
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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: 0.2212 |
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- Wer: 0.2525 |
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- Cer: 0.0565 |
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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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| 0.4436 | 0.0900 | 300 | 0.5638 | 0.5560 | 0.1447 | |
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| 0.5495 | 0.1800 | 600 | 0.6876 | 0.6171 | 0.1641 | |
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| 0.6148 | 0.2699 | 900 | 0.6872 | 0.6211 | 0.1724 | |
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| 0.564 | 0.3599 | 1200 | 0.5503 | 0.5162 | 0.1326 | |
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| 0.4964 | 0.4499 | 1500 | 0.5831 | 0.5319 | 0.1318 | |
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| 0.4437 | 0.5399 | 1800 | 0.4913 | 0.4935 | 0.1202 | |
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| 0.4441 | 0.6299 | 2100 | 0.4754 | 0.4764 | 0.1193 | |
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| 0.3861 | 0.7199 | 2400 | 0.4357 | 0.4361 | 0.1055 | |
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| 0.3811 | 0.8098 | 2700 | 0.4282 | 0.4137 | 0.0976 | |
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| 0.3754 | 0.8998 | 3000 | 0.3905 | 0.4069 | 0.0975 | |
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| 0.3511 | 0.9898 | 3300 | 0.3547 | 0.3692 | 0.0863 | |
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| 0.2496 | 1.0798 | 3600 | 0.3297 | 0.3433 | 0.0796 | |
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| 0.242 | 1.1698 | 3900 | 0.3125 | 0.3315 | 0.0770 | |
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| 0.2378 | 1.2597 | 4200 | 0.3158 | 0.3336 | 0.0757 | |
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| 0.2274 | 1.3497 | 4500 | 0.2871 | 0.3097 | 0.0722 | |
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| 0.2142 | 1.4397 | 4800 | 0.3010 | 0.3058 | 0.0712 | |
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| 0.1949 | 1.5297 | 5100 | 0.2767 | 0.2944 | 0.0678 | |
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| 0.198 | 1.6197 | 5400 | 0.2487 | 0.2824 | 0.0639 | |
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| 0.1806 | 1.7097 | 5700 | 0.2376 | 0.2674 | 0.0612 | |
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| 0.1675 | 1.7996 | 6000 | 0.2293 | 0.2630 | 0.0595 | |
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| 0.1671 | 1.8896 | 6300 | 0.2248 | 0.2581 | 0.0576 | |
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| 0.1526 | 1.9796 | 6600 | 0.2212 | 0.2525 | 0.0565 | |
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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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