original_oomr_800

This model is a fine-tuned version of bert-base-uncased on the ComNum dataset. This model used 800 samples as training, 200 as validation, and 1200 as test on three epochs.

• Loss: 0.3552
• Accuracy: 0.765

This model achieves the following results on the test set:

• Loss: 0.3520
• Accuracy: 0.75

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: 5e-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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	100	0.3559	0.765
No log	2.0	200	0.3547	0.765
No log	3.0	300	0.3552	0.765

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0