distilbert-base-uncased-finetuned-emotion

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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: 0.2144
• Accuracy: 0.9335
• F1: 0.9336

Model description

label0 = sadness label1 = joy label2 = love label3 = anger label4 = fear label5 = surprise

eg: model("I am extremely mesmerised")

output : [{'label': 'LABEL_5', 'score': 0.857551097869873}]

label5 = surprise

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

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3