ASAP_FineTuningBERT_AugV5_k10_task1_organization_fold3

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

• Loss: 10.8751
• Qwk: 0.0026
• Mse: 10.8741
• Rmse: 3.2976

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

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.25	2	13.4837	0.0	13.4825	3.6719
No log	0.5	4	12.3128	0.0	12.3116	3.5088
No log	0.75	6	11.3587	-0.0024	11.3576	3.3701
No log	1.0	8	10.8751	0.0026	10.8741	3.2976

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.2.0
• Tokenizers 0.19.1