distilbert-base-uncased-finetuned-ft1500_norm300_aug5_10_8x_plus_8_10_4x

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0732
• Mse: 4.2926
• Mae: 1.3756
• R2: 0.4728
• Accuracy: 0.3427

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Mae	R2	Accuracy
0.7013	1.0	7652	1.0583	4.2330	1.5178	0.4801	0.2056
0.3648	2.0	15304	1.0732	4.2926	1.3756	0.4728	0.3427

Framework versions

• Transformers 4.21.1
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1