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---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: electra-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split
split: validation
args: split
metrics:
- name: Accuracy
type: accuracy
value: 0.944
---
<!-- 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-emotion
This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1403
- Accuracy: 0.944
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6777 | 1.0 | 500 | 0.2635 | 0.9155 |
| 0.186 | 2.0 | 1000 | 0.1598 | 0.935 |
| 0.113 | 3.0 | 1500 | 0.1403 | 0.944 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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