metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- f1
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-finetuned-go_emotions_20220608_1
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: go_emotions
type: go_emotions
args: simplified
metrics:
- type: f1
value: 0.5575026333429091
name: F1
- type: accuracy
value: 0.43641725027644673
name: Accuracy
distilbert-base-uncased-finetuned-go_emotions_20220608_1
This model is a fine-tuned version of distilbert-base-uncased on the go_emotions dataset. It achieves the following results on the evaluation set:
- Loss: 0.0857
- F1: 0.5575
- Roc Auc: 0.7242
- Accuracy: 0.4364
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.173 | 1.0 | 679 | 0.1074 | 0.4245 | 0.6455 | 0.2976 |
| 0.0989 | 2.0 | 1358 | 0.0903 | 0.5199 | 0.6974 | 0.3972 |
| 0.0865 | 3.0 | 2037 | 0.0868 | 0.5504 | 0.7180 | 0.4263 |
| 0.0806 | 4.0 | 2716 | 0.0860 | 0.5472 | 0.7160 | 0.4233 |
| 0.0771 | 5.0 | 3395 | 0.0857 | 0.5575 | 0.7242 | 0.4364 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1