HW_llama3

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: 0.5763
• eval_matthews_correlation: 0.4248
• eval_runtime: 0.743
• eval_samples_per_second: 1403.799
• eval_steps_per_second: 88.831
• epoch: 1.0
• step: 2138

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: 1.6949202690971937e-05
• train_batch_size: 4
• eval_batch_size: 16
• seed: 2
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Framework versions

• Transformers 4.44.0
• Pytorch 2.3.1+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1