metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: roberta-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: 0.938
roberta-emotion
This model is a fine-tuned version of roberta-base on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1394
- Accuracy: 0.938
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 |
|---|---|---|---|---|
| 0.6103 | 1.0 | 500 | 0.2516 | 0.9195 |
| 0.1981 | 2.0 | 1000 | 0.1747 | 0.9345 |
| 0.1214 | 3.0 | 1500 | 0.1394 | 0.938 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0