llama-3b-irony

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5817
• Accuracy: 0.7105
• F1: 0.6146

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: 0.0002
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	30	1.0633	0.5013	0.5155
No log	2.0	60	0.7927	0.5982	0.5191
No log	3.0	90	0.6772	0.6531	0.5763
No log	4.0	120	0.6298	0.6786	0.5896
No log	5.0	150	0.6055	0.6964	0.6222
No log	6.0	180	0.5919	0.7041	0.5842
No log	7.0	210	0.5895	0.7156	0.6455
No log	8.0	240	0.5849	0.7066	0.6102
No log	9.0	270	0.5831	0.7168	0.6172
No log	10.0	300	0.5817	0.7105	0.6146

Framework versions

• PEFT 0.14.0
• Transformers 4.47.1
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0