sentiment_analysis_bert

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

• Loss: 0.1594
• Accuracy: 0.9445
• F1: 0.9195

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: 16
• eval_batch_size: 16
• 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	F1
0.2274	1.0	1000	0.1954	0.923	0.8946
0.1215	2.0	2000	0.1439	0.9355	0.9064
0.0776	3.0	3000	0.1594	0.9445	0.9195

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Tokenizers 0.13.2