electra-emotion
This model is a fine-tuned version of 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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Model tree for mudogruer/electra-emotion
Base model
google/electra-base-discriminator