Twroberta-baseB_15epoch

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: 0.1971
• Accuracy: 0.7686
• Precision: 0.2328
• Recall: 0.3210
• F1: 0.2693

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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	217	0.1248	0.8571	0.0	0.0	0.0
No log	2.0	434	0.1250	0.8679	0.5258	0.0701	0.1237
0.1617	3.0	651	0.1225	0.825	0.2771	0.2657	0.2712
0.1617	4.0	868	0.1325	0.8079	0.3164	0.2583	0.2554
0.0885	5.0	1085	0.1553	0.7707	0.2169	0.2694	0.2391
0.0885	6.0	1302	0.1680	0.7507	0.2112	0.3358	0.2592
0.0392	7.0	1519	0.2129	0.7093	0.1936	0.3875	0.2575
0.0392	8.0	1736	0.1717	0.7764	0.2316	0.2841	0.2528
0.0392	9.0	1953	0.1915	0.7507	0.2287	0.3321	0.2671
0.0178	10.0	2170	0.1987	0.7586	0.2294	0.3653	0.2809
0.0178	11.0	2387	0.1923	0.7564	0.2287	0.3358	0.2710
0.0108	12.0	2604	0.1925	0.7586	0.2317	0.3358	0.2729
0.0108	13.0	2821	0.1965	0.775	0.2356	0.3284	0.2743
0.0078	14.0	3038	0.1964	0.7621	0.2326	0.3284	0.2712
0.0078	15.0	3255	0.1971	0.7686	0.2328	0.3210	0.2693

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1