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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_Conversation |
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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/pvq9zsxy) |
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# malayalam_combined_Conversation |
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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: 0.9570 |
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- Wer: 0.6223 |
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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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| 1.3673 | 0.6177 | 500 | 1.3771 | 0.7996 | |
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| 1.1485 | 1.2353 | 1000 | 1.2069 | 0.7644 | |
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| 1.0712 | 1.8530 | 1500 | 1.1157 | 0.7296 | |
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| 1.0101 | 2.4707 | 2000 | 1.0969 | 0.7344 | |
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| 0.9326 | 3.0883 | 2500 | 1.0566 | 0.6889 | |
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| 0.8723 | 3.7060 | 3000 | 1.0339 | 0.6861 | |
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| 0.8198 | 4.3237 | 3500 | 1.0028 | 0.6830 | |
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| 0.8092 | 4.9413 | 4000 | 1.0108 | 0.6681 | |
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| 0.7574 | 5.5590 | 4500 | 1.0049 | 0.6676 | |
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| 0.7027 | 6.1767 | 5000 | 0.9725 | 0.6660 | |
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| 0.6981 | 6.7943 | 5500 | 0.9649 | 0.6653 | |
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| 0.6684 | 7.4120 | 6000 | 0.9500 | 0.6393 | |
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| 0.6295 | 8.0296 | 6500 | 0.9535 | 0.6364 | |
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| 0.5947 | 8.6473 | 7000 | 0.9522 | 0.6338 | |
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| 0.5483 | 9.2650 | 7500 | 0.9821 | 0.6262 | |
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| 0.5437 | 9.8826 | 8000 | 0.9570 | 0.6223 | |
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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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