metadata
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: trueparagraph.ai-ELECTRA
results: []
trueparagraph.ai-ELECTRA
This model is a fine-tuned version of google/electra-base-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.9430
- F1: 0.9421
- Precision: 0.9528
- Recall: 0.9316
- Mcc: 0.8862
- Roc Auc: 0.9429
- Pr Auc: 0.9217
- Log Loss: 0.8825
- Loss: 0.2952
Model description
More information needed
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Precision | Recall | Mcc | Roc Auc | Pr Auc | Log Loss | Validation Loss |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5401 | 0.6297 | 500 | 0.7694 | 0.7044 | 0.9732 | 0.5519 | 0.5963 | 0.7684 | 0.7602 | 3.5789 | 0.6109 |
| 0.3122 | 1.2594 | 1000 | 0.9225 | 0.9231 | 0.9122 | 0.9342 | 0.8452 | 0.9225 | 0.8850 | 1.1485 | 0.2368 |
| 0.2301 | 1.8892 | 1500 | 0.8670 | 0.8811 | 0.7942 | 0.9892 | 0.7573 | 0.8676 | 0.7910 | 1.9476 | 0.3654 |
| 0.1608 | 2.5189 | 2000 | 0.9348 | 0.9364 | 0.9103 | 0.9639 | 0.8711 | 0.9349 | 0.8955 | 1.0090 | 0.2677 |
| 0.1146 | 3.1486 | 2500 | 0.9430 | 0.9421 | 0.9528 | 0.9316 | 0.8862 | 0.9429 | 0.9217 | 0.8825 | 0.2952 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1