metadata
license: mit
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- f1
model-index:
- name: emotion_classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: go_emotions
type: go_emotions
config: simplified
split: validation
args: simplified
metrics:
- name: F1
type: f1
value: 0.019548365352207615
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: 2.7211
- F1: 0.0195
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 32 | 2.7963 | 0.0195 |
| No log | 2.0 | 64 | 2.7211 | 0.0195 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3