training_model

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

• Loss: 0.8963
• Accuracy: 0.2903

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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	8	0.9177	0.3548
No log	2.0	16	0.8915	0.3548
No log	3.0	24	0.8937	0.2903
No log	4.0	32	0.8963	0.2903

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1+cpu
• Datasets 2.14.5
• Tokenizers 0.11.0