results

This model is a fine-tuned version of albert-base-v2 on the emotion dataset. It achieves the following results on the evaluation set:

• Loss: 0.2314
• Accuracy: 0.9305

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: 2.8e-05
• train_batch_size: 4
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4298	1.0	4000	0.4243	0.9085
0.2389	2.0	8000	0.3465	0.922
0.1856	3.0	12000	0.2700	0.929

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2