bert-base-uncased_token_itr0_0.0001_all_01_03_2022-14_21_25

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2698
• Precision: 0.3321
• Recall: 0.5265
• F1: 0.4073
• Accuracy: 0.8942

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: 0.0001
• 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	30	0.3314	0.1627	0.3746	0.2269	0.8419
No log	2.0	60	0.2957	0.2887	0.4841	0.3617	0.8592
No log	3.0	90	0.2905	0.2429	0.5141	0.3299	0.8651
No log	4.0	120	0.2759	0.3137	0.5565	0.4013	0.8787
No log	5.0	150	0.2977	0.3116	0.5565	0.3995	0.8796

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.1+cu113
• Datasets 1.18.0
• Tokenizers 0.10.3