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--- |
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license: apache-2.0 |
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base_model: google/muril-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: punjabi-muril-ner |
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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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# punjabi-muril-ner |
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This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0654 |
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- Precision: 0.7923 |
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- Recall: 0.8113 |
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- F1: 0.8017 |
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- Accuracy: 0.9859 |
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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: 2e-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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.3366 | 1.0 | 1613 | 0.2698 | 0.0 | 0.0 | 0.0 | 0.9551 | |
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| 0.1552 | 2.0 | 3226 | 0.1180 | 0.7114 | 0.4972 | 0.5853 | 0.9763 | |
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| 0.0959 | 3.0 | 4839 | 0.0904 | 0.7262 | 0.7161 | 0.7211 | 0.9829 | |
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| 0.0708 | 4.0 | 6452 | 0.0751 | 0.7679 | 0.7498 | 0.7587 | 0.9840 | |
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| 0.0474 | 5.0 | 8065 | 0.0672 | 0.7907 | 0.7731 | 0.7818 | 0.9854 | |
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| 0.0367 | 6.0 | 9678 | 0.0627 | 0.7870 | 0.8045 | 0.7957 | 0.9856 | |
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| 0.0308 | 7.0 | 11291 | 0.0598 | 0.7942 | 0.7915 | 0.7928 | 0.9859 | |
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| 0.0247 | 8.0 | 12904 | 0.0612 | 0.7891 | 0.8123 | 0.8005 | 0.9860 | |
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| 0.0202 | 9.0 | 14517 | 0.0666 | 0.8015 | 0.8015 | 0.8015 | 0.9860 | |
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| 0.0181 | 10.0 | 16130 | 0.0654 | 0.7923 | 0.8113 | 0.8017 | 0.9859 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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