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:

• eval_loss: 0.1710
• eval_accuracy: 0.9295
• eval_f1: 0.9302
• eval_runtime: 11.2289
• eval_samples_per_second: 178.112
• eval_steps_per_second: 2.85
• epoch: 1.0
• step: 250

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

Framework versions

• Transformers 4.33.3
• Pytorch 2.2.0.dev20231211
• Datasets 2.15.0
• Tokenizers 0.11.0