BERT_test_graident_accumulation_test3_finetuned

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.8780
• Accuracy: 0.55

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: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.97	30	0.8294	0.6
No log	1.98	61	0.8516	0.55
No log	2.91	90	0.8780	0.55

Framework versions

• Transformers 4.36.0
• Pytorch 2.1.1+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0