norbert2_sentiment_norec_13

This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6303
• Compute Metrics: :
• Accuracy: 0.6
• Balanced Accuracy: 0.375
• F1 Score: 0.75
• Recall: 0.75
• Precision: 0.75

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: 5e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Compute Metrics	Accuracy	Balanced Accuracy	F1 Score	Recall	Precision
0.6492	1.0	3	0.6466	:	0.6	0.375	0.75	0.75	0.75
0.3086	2.0	6	0.6303	:	0.6	0.375	0.75	0.75	0.75

Framework versions

• Transformers 4.26.0
• Pytorch 1.13.1+cu117
• Datasets 2.9.0
• Tokenizers 0.13.2