lab9_model_bert

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: 0.6498

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	50	3.6137
No log	2.0	100	1.9421
No log	3.0	150	1.2792
No log	4.0	200	1.0015
No log	5.0	250	0.8056
No log	6.0	300	0.7624
No log	7.0	350	0.6635
No log	8.0	400	0.6740
No log	9.0	450	0.6580
1.4267	10.0	500	0.6498

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.8.0
• Tokenizers 0.13.2