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---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: electra_multiple_choice
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_multiple_choice
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: 1.6404
- Accuracy: 0.4
## 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-06
- 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
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4566 | 1.0 | 1724 | 1.3690 | 0.3 |
| 1.2925 | 2.0 | 3448 | 1.3269 | 0.4 |
| 1.1812 | 3.0 | 5172 | 1.3479 | 0.35 |
| 1.0807 | 4.0 | 6896 | 1.3464 | 0.35 |
| 0.9799 | 5.0 | 8620 | 1.3757 | 0.4 |
| 0.8792 | 6.0 | 10344 | 1.5018 | 0.45 |
| 0.7843 | 7.0 | 12068 | 1.6404 | 0.4 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3