<!-- 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. -->
emotion_classification
This model is a fine-tuned version of roberta-base on the go_emotions dataset. It achieves the following results on the evaluation set:
- Loss: 1.6119
- F1: 0.3852
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 313 | 1.8826 | 0.1762 |
| 2.1614 | 2.0 | 626 | 1.6738 | 0.3442 |
| 2.1614 | 3.0 | 939 | 1.6119 | 0.3852 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
