metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: distilroberta-emotion-intent
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9435
distilroberta-emotion-intent
This model is a fine-tuned version of distilroberta-base on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1496
- Accuracy: 0.9435
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: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4501 | 1.0 | 1000 | 0.2432 | 0.924 |
| 0.1947 | 2.0 | 2000 | 0.1646 | 0.934 |
| 0.1497 | 3.0 | 3000 | 0.1382 | 0.9405 |
| 0.1316 | 4.0 | 4000 | 0.1496 | 0.9435 |
| 0.1145 | 5.0 | 5000 | 0.1684 | 0.9385 |
| 0.1 | 6.0 | 6000 | 0.2342 | 0.943 |
| 0.0828 | 7.0 | 7000 | 0.2807 | 0.939 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1