tk648
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distilbert-base-uncased-finetuned-emotion

Text Classification

Generated from Trainer

Eval Results (legacy)

text-embeddings-inference

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distilbert-base-uncased-finetuned-emotion

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: 0.2221
Accuracy: 0.9215
F1: 0.9217

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.8339	1.0	250	0.3233	0.903	0.9009
0.2517	2.0	500	0.2221	0.9215	0.9217

Framework versions

Transformers 4.20.1
Pytorch 1.12.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1

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Dataset used to train tk648/distilbert-base-uncased-finetuned-emotion

Evaluation results

Accuracy on emotion
self-reported

0.921
F1 on emotion
self-reported

0.922