deberta-finetuned-claimdecomp

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

• Loss: 1.7521
• Accuracy: 0.205

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 30000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.7301	50.0	5000	1.7496	0.205
1.7267	100.0	10000	1.7525	0.205
1.7277	150.0	15000	1.7508	0.205
1.7278	200.0	20000	1.7508	0.205
1.7222	250.0	25000	1.7506	0.205
1.725	300.0	30000	1.7521	0.205

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1