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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-S800
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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-S800
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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: 0.0720
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- Precision: 0.6206
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- Recall: 0.6999
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- F1: 0.6579
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- Accuracy: 0.9749
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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 | 55 | 0.0995 | 0.4306 | 0.3829 | 0.4053 | 0.9649 |
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| No log | 2.0 | 110 | 0.0732 | 0.5802 | 0.6494 | 0.6128 | 0.9723 |
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| No log | 3.0 | 165 | 0.0694 | 0.5870 | 0.6957 | 0.6367 | 0.9735 |
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| No log | 4.0 | 220 | 0.0700 | 0.6161 | 0.6957 | 0.6535 | 0.9749 |
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| No log | 5.0 | 275 | 0.0720 | 0.6206 | 0.6999 | 0.6579 | 0.9749 |
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### Framework versions
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- Transformers 4.33.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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