bert-base-cased-english-sentweet-Targeted-Insult

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.7559
• Accuracy: 0.8021
• Precision: 0.8122
• Recall: 0.8108
• F1: 0.8021

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	81	0.4820	0.8090	0.8323	0.8219	0.8085
No log	2.0	162	0.4688	0.8229	0.8441	0.8352	0.8226
No log	3.0	243	0.5383	0.8056	0.8185	0.8153	0.8055
No log	4.0	324	0.5501	0.8056	0.8148	0.8139	0.8055
No log	5.0	405	0.6789	0.7847	0.7883	0.7902	0.7846
No log	6.0	486	0.7559	0.8021	0.8122	0.8108	0.8021

Framework versions

• Transformers 4.24.0
• Pytorch 1.13.1+cu117
• Datasets 2.6.1
• Tokenizers 0.11.0