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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: w2v-bert-2.0-tamil-gpu-custom_v10 |
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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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# w2v-bert-2.0-tamil-gpu-custom_v10 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 0.4032 |
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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: 4.43567e-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: 500 |
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- num_epochs: 5 |
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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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| 2.4046 | 0.24 | 300 | inf | 0.3596 | |
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| 0.5204 | 0.49 | 600 | inf | 0.3451 | |
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| 0.4297 | 0.73 | 900 | inf | 0.3272 | |
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| 0.3891 | 0.97 | 1200 | inf | 0.3477 | |
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| 0.6568 | 1.22 | 1500 | inf | 0.3937 | |
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| 0.862 | 1.46 | 1800 | inf | 0.4033 | |
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| 0.9171 | 1.71 | 2100 | inf | 0.4032 | |
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| 0.9643 | 1.95 | 2400 | inf | 0.4032 | |
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| 0.9568 | 2.19 | 2700 | inf | 0.4032 | |
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| 0.8953 | 2.44 | 3000 | inf | 0.4032 | |
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| 0.9372 | 2.68 | 3300 | inf | 0.4032 | |
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| 0.9671 | 2.92 | 3600 | inf | 0.4032 | |
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| 0.9527 | 3.17 | 3900 | inf | 0.4032 | |
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| 0.8851 | 3.41 | 4200 | inf | 0.4032 | |
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| 0.8781 | 3.65 | 4500 | inf | 0.4032 | |
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| 0.8971 | 3.9 | 4800 | inf | 0.4032 | |
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| 0.8623 | 4.14 | 5100 | inf | 0.4032 | |
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| 0.9137 | 4.38 | 5400 | inf | 0.4032 | |
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| 0.8969 | 4.63 | 5700 | inf | 0.4032 | |
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| 0.8769 | 4.87 | 6000 | inf | 0.4032 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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