lora-roberta-base-finetuned-captures

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

• Loss: 0.2959
• Accuracy: 0.9127

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: 0.0003
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2353	0.9994	772	0.3571	0.9003
0.228	2.0	1545	0.3288	0.9072
0.2426	2.9994	2317	0.3198	0.9092
0.213	4.0	3090	0.2959	0.9127
0.1172	4.9968	3860	0.2959	0.9120

Framework versions

• PEFT 0.12.0
• Transformers 4.40.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.0