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--- |
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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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metrics: |
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- wer |
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model-index: |
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- name: malayalam_combined_Extempore |
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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/krishnan-aravind/huggingface/runs/xe6xq146) |
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# malayalam_combined_Extempore |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4866 |
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- Wer: 0.4837 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 10 |
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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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| 0.8139 | 0.9794 | 500 | 0.8389 | 0.6821 | |
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| 0.6539 | 1.9589 | 1000 | 0.6815 | 0.6041 | |
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| 0.5383 | 2.9383 | 1500 | 0.5827 | 0.5705 | |
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| 0.4772 | 3.9177 | 2000 | 0.5398 | 0.5548 | |
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| 0.4351 | 4.8972 | 2500 | 0.5342 | 0.5407 | |
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| 0.3866 | 5.8766 | 3000 | 0.5411 | 0.5174 | |
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| 0.3567 | 6.8560 | 3500 | 0.5063 | 0.5085 | |
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| 0.3047 | 7.8355 | 4000 | 0.4886 | 0.4986 | |
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| 0.2879 | 8.8149 | 4500 | 0.4878 | 0.4884 | |
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| 0.2648 | 9.7943 | 5000 | 0.4866 | 0.4837 | |
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### Framework versions |
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- Transformers 4.43.0.dev0 |
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- Pytorch 1.14.0a0+44dac51 |
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- Datasets 2.16.1 |
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- Tokenizers 0.19.1 |
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