TrainingArg

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

• Loss: 1.9255
• Accuracy: 0.6636

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: 12
• eval_batch_size: 12
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	74	1.2499	0.4864
No log	2.0	148	1.1182	0.6227
No log	3.0	222	1.2290	0.5409
No log	4.0	296	1.1244	0.6273
No log	5.0	370	1.2734	0.6545
No log	6.0	444	1.6389	0.6045
0.6739	7.0	518	1.5203	0.6636
0.6739	8.0	592	1.8517	0.6227
0.6739	9.0	666	1.8682	0.6591
0.6739	10.0	740	1.9589	0.6364
0.6739	11.0	814	1.9143	0.6545
0.6739	12.0	888	1.9255	0.6636

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1