nlp_til2

This model is a fine-tuned version of casual/nlp_til2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0041
• Precision: 0.9920
• Recall: 0.9923
• F1: 0.9921
• Accuracy: 0.9987

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: 2e-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: 18

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	219	0.0286	0.9350	0.9281	0.9316	0.9896
No log	2.0	438	0.0277	0.9439	0.9235	0.9336	0.9899
0.0365	3.0	657	0.0296	0.9127	0.9300	0.9213	0.9890
0.0365	4.0	876	0.0267	0.9232	0.9404	0.9317	0.9900
0.0332	5.0	1095	0.0205	0.9451	0.9599	0.9524	0.9929
0.0332	6.0	1314	0.0165	0.9725	0.9542	0.9633	0.9942
0.0293	7.0	1533	0.0145	0.9729	0.9579	0.9653	0.9946
0.0293	8.0	1752	0.0156	0.9577	0.9658	0.9617	0.9944
0.0293	9.0	1971	0.0111	0.9756	0.9737	0.9746	0.9961
0.0237	10.0	2190	0.0091	0.9773	0.9803	0.9788	0.9968
0.0237	11.0	2409	0.0088	0.9750	0.9803	0.9777	0.9968
0.0199	12.0	2628	0.0068	0.9888	0.9848	0.9868	0.9978
0.0199	13.0	2847	0.0070	0.9835	0.9847	0.9841	0.9977
0.0201	14.0	3066	0.0074	0.9834	0.9861	0.9848	0.9976
0.0201	15.0	3285	0.0051	0.9869	0.9889	0.9879	0.9983
0.0257	16.0	3504	0.0040	0.9921	0.9913	0.9917	0.9987
0.0257	17.0	3723	0.0045	0.9911	0.9922	0.9916	0.9987
0.0257	18.0	3942	0.0041	0.9920	0.9923	0.9921	0.9987

Framework versions

• Transformers 4.40.2
• Pytorch 2.0.1+cu117
• Datasets 2.19.1
• Tokenizers 0.19.1