llama31-tweeteval-offensive-qlora

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

qlora

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the tweeteval_offensive_train dataset. It achieves the following results on the evaluation set:

• Loss: 0.1415

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: 4
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 3.0

Training results

Framework versions

• PEFT 0.17.1
• Transformers 4.57.1
• Pytorch 2.9.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.1