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---
license: apache-2.0
base_model: google/electra-small-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: electra-small-discriminator-zeroshot-v1.1-none
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-small-discriminator-zeroshot-v1.1-none
This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3747
- F1 Macro: 0.4125
- F1 Micro: 0.4620
- Accuracy Balanced: 0.4701
- Accuracy: 0.4620
- Precision Macro: 0.5162
- Recall Macro: 0.4701
- Precision Micro: 0.4620
- Recall Micro: 0.4620
## 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: 64
- eval_batch_size: 64
- seed: 80085
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.04
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| 0.4765 | 0.32 | 5000 | 0.5300 | 0.7326 | 0.7528 | 0.7329 | 0.7528 | 0.7322 | 0.7329 | 0.7528 | 0.7528 |
| 0.4408 | 0.65 | 10000 | 0.5099 | 0.7402 | 0.765 | 0.7359 | 0.765 | 0.7463 | 0.7359 | 0.765 | 0.765 |
| 0.4169 | 0.97 | 15000 | 0.4976 | 0.7473 | 0.7702 | 0.7439 | 0.7702 | 0.7517 | 0.7439 | 0.7702 | 0.7702 |
| 0.387 | 1.3 | 20000 | 0.4943 | 0.7525 | 0.7742 | 0.7498 | 0.7742 | 0.7559 | 0.7498 | 0.7742 | 0.7742 |
| 0.3905 | 1.62 | 25000 | 0.4931 | 0.7522 | 0.775 | 0.7484 | 0.775 | 0.7572 | 0.7484 | 0.775 | 0.775 |
| 0.4001 | 1.95 | 30000 | 0.4924 | 0.7544 | 0.7752 | 0.7524 | 0.7752 | 0.7568 | 0.7524 | 0.7752 | 0.7752 |
| 0.3995 | 2.27 | 35000 | 0.4900 | 0.7543 | 0.7758 | 0.7517 | 0.7758 | 0.7576 | 0.7517 | 0.7758 | 0.7758 |
| 0.3981 | 2.6 | 40000 | 0.4906 | 0.7529 | 0.7742 | 0.7504 | 0.7742 | 0.7558 | 0.7504 | 0.7742 | 0.7742 |
| 0.4232 | 2.92 | 45000 | 0.4904 | 0.7544 | 0.776 | 0.7516 | 0.776 | 0.7579 | 0.7516 | 0.776 | 0.776 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.13.3
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