intent_classfication2

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

• Loss: 0.1321
• Accuracy: 0.9618

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6215	1.0	655	1.0384	0.8342
1.0518	2.0	1310	0.5333	0.8892
0.676	3.0	1965	0.3383	0.9228
0.3837	4.0	2620	0.2589	0.9373
0.3307	5.0	3275	0.2148	0.9415
0.2926	6.0	3930	0.1872	0.9492
0.2465	7.0	4585	0.1698	0.9530
0.2338	8.0	5240	0.1585	0.9553
0.2156	9.0	5895	0.1486	0.9599
0.2078	10.0	6550	0.1429	0.9603
0.2	11.0	7205	0.1392	0.9603
0.1973	12.0	7860	0.1362	0.9614
0.184	13.0	8515	0.1339	0.9622
0.1884	14.0	9170	0.1326	0.9622
0.1871	15.0	9825	0.1321	0.9618

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0