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End of training

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README.md ADDED
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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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+
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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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+
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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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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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