test_trainer

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

• Loss: 0.3749
• Accuracy: {'accuracy': 0.8666666666666667}

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: 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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	68	0.6762	{'accuracy': 0.562962962962963}
No log	2.0	136	0.6068	{'accuracy': 0.7185185185185186}
No log	3.0	204	0.5367	{'accuracy': 0.7777777777777778}
No log	4.0	272	0.7216	{'accuracy': 0.562962962962963}
No log	5.0	340	0.7669	{'accuracy': 0.6814814814814815}
No log	6.0	408	0.4202	{'accuracy': 0.8592592592592593}
No log	7.0	476	0.3749	{'accuracy': 0.8666666666666667}

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cpu
• Datasets 2.16.1
• Tokenizers 0.14.1