sentence_sentiments_analysis_bert

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

• Loss: 0.3401
• F1-score: 0.9007

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1-score
0.3194	1.0	2500	0.3401	0.9007
0.232	2.0	5000	0.3748	0.9126
0.1364	3.0	7500	0.4277	0.9186
0.0537	4.0	10000	0.4881	0.9214
0.0238	5.0	12500	0.5175	0.9240

Framework versions

• Transformers 4.32.1
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3