distilbert-base-uncased-lora-text-classification

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

• eval_loss: 0.7425
• eval_accuracy: {'accuracy': 0.888}
• eval_runtime: 219.3112
• eval_samples_per_second: 4.56
• eval_steps_per_second: 1.14
• epoch: 5.0
• step: 1250

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: 0.001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Framework versions

• PEFT 0.11.1
• Transformers 4.41.1
• Pytorch 2.3.0+cpu
• Datasets 2.19.1
• Tokenizers 0.19.1