metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - go_emotions
metrics:
  - f1
  - accuracy
model-index:
  - name: distilbert-base-uncased-finetuned-go_emotions_20220608_1
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: go_emotions
          type: go_emotions
          args: simplified
        metrics:
          - name: F1
            type: f1
            value: 0.5575026333429091
          - name: Accuracy
            type: accuracy
            value: 0.43641725027644673

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