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--- |
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license: mit |
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base_model: prajjwal1/bert-tiny |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: fine_tune_bert_output |
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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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# fine_tune_bert_output |
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0094 |
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- Overall Precision: 0.9722 |
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- Overall Recall: 0.9722 |
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- Overall F1: 0.9722 |
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- Overall Accuracy: 0.9963 |
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- Number Of Employees F1: 0.9722 |
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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: 0.0002 |
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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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- 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: 150 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Number Of Employees F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:----------------------:| |
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| 0.0011 | 50.0 | 1000 | 0.0046 | 0.9722 | 0.9722 | 0.9722 | 0.9963 | 0.9722 | |
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| 0.0003 | 100.0 | 2000 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0002 | 150.0 | 3000 | 0.0094 | 0.9722 | 0.9722 | 0.9722 | 0.9963 | 0.9722 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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