bert-base-cased-finetuned-products

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: 2.1250

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: 4e-05
• train_batch_size: 8
• eval_batch_size: 8
• 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
7.1574	1.0	7595	6.0100
4.7853	2.0	15190	3.7723
3.0734	3.0	22785	2.7345
2.2249	4.0	30380	2.2894
1.746	5.0	37975	2.0801
1.4232	6.0	45570	1.9818
1.177	7.0	53165	1.9314
0.9785	8.0	60760	1.9254
0.8097	9.0	68355	1.9443
0.6691	10.0	75950	1.9722
0.5536	11.0	83545	2.0024
0.4616	12.0	91140	2.0540
0.3869	13.0	98735	2.0819
0.3302	14.0	106330	2.1114
0.2915	15.0	113925	2.1250

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0.post100
• Datasets 2.19.1
• Tokenizers 0.19.1