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README.md
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---
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license: apache-2.0
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base_model: google/electra-base-discriminator
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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: electra-finetuned-ner-copious
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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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# electra-finetuned-ner-copious
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This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0614
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- Precision: 0.7361
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- Recall: 0.7681
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- F1: 0.7518
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- Accuracy: 0.9814
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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: 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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| No log | 1.0 | 63 | 0.0999 | 0.4927 | 0.4870 | 0.4898 | 0.9675 |
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| No log | 2.0 | 126 | 0.0677 | 0.6728 | 0.7420 | 0.7057 | 0.9783 |
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| No log | 3.0 | 189 | 0.0648 | 0.7153 | 0.7101 | 0.7127 | 0.9795 |
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| No log | 4.0 | 252 | 0.0619 | 0.7299 | 0.7638 | 0.7465 | 0.9809 |
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| No log | 5.0 | 315 | 0.0614 | 0.7361 | 0.7681 | 0.7518 | 0.9814 |
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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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