| --- |
| license: apache-2.0 |
| base_model: google/electra-base-discriminator |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: electra-finetuned-ner-copious |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # electra-finetuned-ner-copious |
|
|
| This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0614 |
| - Precision: 0.7361 |
| - Recall: 0.7681 |
| - F1: 0.7518 |
| - Accuracy: 0.9814 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 63 | 0.0999 | 0.4927 | 0.4870 | 0.4898 | 0.9675 | |
| | No log | 2.0 | 126 | 0.0677 | 0.6728 | 0.7420 | 0.7057 | 0.9783 | |
| | No log | 3.0 | 189 | 0.0648 | 0.7153 | 0.7101 | 0.7127 | 0.9795 | |
| | No log | 4.0 | 252 | 0.0619 | 0.7299 | 0.7638 | 0.7465 | 0.9809 | |
| | No log | 5.0 | 315 | 0.0614 | 0.7361 | 0.7681 | 0.7518 | 0.9814 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.33.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
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|
