metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - f1
  - accuracy
model-index:
  - name: distilbert-base-uncased-finetuned-with-emotions
    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: 0.9382291479360674
          - name: Accuracy
            type: accuracy
            value: 0.938

distilbert-base-uncased-finetuned-with-emotions

This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.1503
F1: 0.9382
Accuracy: 0.938

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: 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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.1289	1.0	250	0.1653	0.9414	0.9405
0.0744	2.0	500	0.1503	0.9382	0.938

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1