bert-base-uncased_token_itr0_2e-05_all_01_03_2022-04_40_10

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: 0.2741
• Precision: 0.1936
• Recall: 0.3243
• F1: 0.2424
• Accuracy: 0.8764

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: 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	0.3235	0.1062	0.2076	0.1405	0.8556
No log	2.0	60	0.2713	0.1710	0.3080	0.2199	0.8872
No log	3.0	90	0.3246	0.2010	0.3391	0.2524	0.8334
No log	4.0	120	0.3008	0.2011	0.3685	0.2602	0.8459
No log	5.0	150	0.2714	0.1780	0.3772	0.2418	0.8661

Framework versions

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