metadata

license: apache-2.0
datasets:
  - dair-ai/emotion
language:
  - en
metrics:
  - f1
  - accuracy
base_model:
  - distilbert-base-uncased
library_name: transformers
pipeline_tag: text-classification
tags:
  - distilbert
  - pytorch
  - emotion
  - trainer
widget:
  - text: >-
      Interview preparation, I hate talking about myself, one dull subject
      matter!
  - text: >-
      I'm in such a happy mood today i feel almost delighted and i havent done
      anything different today then i normally have it is wonderful
  - text: >-
      I had every intention of doing more gardening this morning while it was
      still cool but i was just feeling so rotten
  - text: >-
      Wow! I'm really impressed that Ashley can speak 7 languages, whereas I
      only speak one!
  - text: >-
      No one wants to win the wild card because you have to play the Cubs on the
      road.
  - text: >-
      After Kylie had her heart broken by her ex-boyfriend, she felt so down and
      blue. I tried to cheer her up, but she just wants to be sad for awhile.
  - text: >-
      Jamie was in a bar with his friends one night when he saw a beautiful
      girl. He felt confident that night so he went to go talk to her.

distilbert-base-uncased-finetuned-emotion

This model is a fine-tuned variant of distilbert-base-uncased using the emotion dataset. The evaluation results demonstrate its performance:

Loss: 0.1595
Accuracy: 93.35%
F1 Score: 93.35%

Hyperparameters

learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
lr_scheduler_type: linear
num_epochs: 2

Training results

Epoch	Training Loss	Validation Loss	Accuracy	F1
1	0.1703	0.1709	0.9355	0.9361
2	0.1115	0.1595	0.9335	0.9335