metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- f1
model-index:
- name: deberta-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split
split: validation
args: split
metrics:
- name: F1
type: f1
value: 0.9352884200987154
deberta-emotion
This model is a fine-tuned version of microsoft/deberta-v3-base on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1592
- F1: 0.9353
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.1784 | 1.0 | 250 | 0.1746 | 0.9325 |
| 0.1273 | 2.0 | 500 | 0.1672 | 0.9332 |
| 0.1008 | 3.0 | 750 | 0.1592 | 0.9353 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2