POCQ_tr

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: 0.3264

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: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss
0.4013	1.0	208	0.3534
0.2589	2.0	416	0.3264
0.1960	3.0	624	0.4001
0.0987	4.0	832	0.5516

Framework versions

• Transformers 5.16.1
• Pytorch 2.14.0+cpu
• Datasets 5.0.1
• Tokenizers 0.23.2