correct_BERT_token_itr0_0.0001_webDiscourse_01_03_2022-15_47_14

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: 0.6542
• Precision: 0.0092
• Recall: 0.0403
• F1: 0.0150
• Accuracy: 0.7291

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	10	0.5856	0.0012	0.0125	0.0022	0.6950
No log	2.0	20	0.5933	0.0	0.0	0.0	0.7282
No log	3.0	30	0.5729	0.0051	0.025	0.0085	0.7155
No log	4.0	40	0.6178	0.0029	0.0125	0.0047	0.7143
No log	5.0	50	0.6707	0.0110	0.0375	0.0170	0.7178

Framework versions

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