End of training
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- model.safetensors +1 -1
README.md
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name: ner
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type: ner
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config: indian_names
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split:
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args: indian_names
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metrics:
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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- name: F1
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type: f1
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value: 0.
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- name: Accuracy
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type: accuracy
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value: 0.
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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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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ner dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.9837
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- Accuracy: 0.
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## Model description
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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:
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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.
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### Framework versions
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name: ner
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type: ner
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config: indian_names
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split: test
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args: indian_names
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metrics:
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- name: Precision
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type: precision
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value: 0.9752319346327347
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- name: Recall
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type: recall
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value: 0.9923783128356141
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- name: F1
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type: f1
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value: 0.9837304142519855
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- name: Accuracy
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type: accuracy
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value: 0.9730393535444438
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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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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ner dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1205
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- Precision: 0.9752
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- Recall: 0.9924
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- F1: 0.9837
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- Accuracy: 0.9730
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## Model description
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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: 5
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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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| 0.0825 | 1.0 | 501 | 0.1031 | 0.9600 | 0.9917 | 0.9756 | 0.9770 |
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| 0.0337 | 2.0 | 1002 | 0.1491 | 0.9615 | 0.9942 | 0.9776 | 0.9648 |
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| 0.0285 | 3.0 | 1503 | 0.1169 | 0.9754 | 0.9913 | 0.9833 | 0.9723 |
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| 0.0249 | 4.0 | 2004 | 0.1054 | 0.9724 | 0.9921 | 0.9821 | 0.9783 |
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| 0.0232 | 5.0 | 2505 | 0.1205 | 0.9752 | 0.9924 | 0.9837 | 0.9730 |
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### Framework versions
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model.safetensors
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