twitter-roberta-base_3epoch10.32

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-irony on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.2125
• Accuracy: 0.7450
• F1: 0.4
• Precision: 0.6146
• Recall: 0.2965
• Precision Sarcastic: 0.6146
• Recall Sarcastic: 0.2965
• F1 Sarcastic: 0.4

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Precision Sarcastic	Recall Sarcastic	F1 Sarcastic
No log	1.0	87	1.9011	0.7464	0.5138	0.5706	0.4673	0.5706	0.4673	0.5138
No log	2.0	174	2.0529	0.7579	0.4510	0.6449	0.3467	0.6449	0.3467	0.4510
No log	3.0	261	1.6275	0.7594	0.4862	0.6270	0.3970	0.6270	0.3970	0.4862
No log	4.0	348	2.1947	0.7550	0.3796	0.6933	0.2613	0.6933	0.2613	0.3796
No log	5.0	435	1.9559	0.7522	0.4971	0.5944	0.4271	0.5944	0.4271	0.4971
0.0241	6.0	522	2.1438	0.7478	0.3902	0.6364	0.2814	0.6364	0.2814	0.3902
0.0241	7.0	609	2.0612	0.7550	0.4817	0.6124	0.3970	0.6124	0.3970	0.4817
0.0241	8.0	696	2.1265	0.7565	0.4601	0.6316	0.3618	0.6316	0.3618	0.4601
0.0241	9.0	783	2.2016	0.7464	0.4054	0.6186	0.3015	0.6186	0.3015	0.4054
0.0241	10.0	870	2.2125	0.7450	0.4	0.6146	0.2965	0.6146	0.2965	0.4

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1