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 SetFit/emotion. It achieves the following results on the evaluation set:

• Loss: 0.2276
• Accuracy: 0.921
• F1: 0.9209

Model description

This model follows chapter 2 of https://github.com/nlp-with-transformers/notebooks. A few things that were changed from the original notebook:

• the emotion dataset has moved to SetFit/emotion https://github.com/nlp-with-transformers/notebooks/issues/77
• the new dataset doesn't have ClassLabel feature so needed to change int2str method https://github.com/nlp-with-transformers/notebooks/issues/77
• made the label names on inference API human-readable with https://discuss.huggingface.co/t/change-label-names-on-inference-api/3063/3
• function to inspect dataset for existence of certain strings

Intended uses & limitations

Training and evaluation data

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 4.13.0
• Pytorch 1.13.0+cu116
• Datasets 1.16.1
• Tokenizers 0.10.3