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: 0.1443
• Accuracy: 0.9375
• F1: 0.9378

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: 256
• eval_batch_size: 256
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	63	0.8657	0.714	0.6520
No log	2.0	126	0.3186	0.9085	0.9076
No log	3.0	189	0.2032	0.928	0.9281
0.5856	4.0	252	0.1733	0.93	0.9301
0.5856	5.0	315	0.1578	0.937	0.9368
0.5856	6.0	378	0.1543	0.9335	0.9341
0.5856	7.0	441	0.1506	0.9345	0.9343
0.1139	8.0	504	0.1475	0.939	0.9396
0.1139	9.0	567	0.1444	0.9375	0.9374
0.1139	10.0	630	0.1443	0.9375	0.9378

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1