metadata
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: electra-base-multiple-choice-fp16-v2
results: []
electra-base-multiple-choice-fp16-v2
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:
- Loss: 0.2950
- Accuracy: 0.8960
- Precision: 0.8927
- Recall: 0.9003
- F1: 0.8965
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: 2e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 269 | 0.2875 | 0.8818 | 0.8846 | 0.8782 | 0.8814 |
| 0.3437 | 2.0 | 538 | 0.2862 | 0.8917 | 0.8912 | 0.8924 | 0.8918 |
| 0.3437 | 3.0 | 807 | 0.2950 | 0.8960 | 0.8927 | 0.9003 | 0.8965 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0