distilled-llama-sst2

This model is a fine-tuned version of NousResearch/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3580
• Accuracy: 0.9278
• F1: 0.9310
• Precision: 0.9062
• Recall: 0.9572

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• 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
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.3856	0.2375	1000	0.3681	0.9243	0.9273	0.9073	0.9482
0.3681	0.4751	2000	0.3634	0.9266	0.9297	0.9077	0.9527
0.3648	0.7126	3000	0.3599	0.9346	0.9366	0.9253	0.9482
0.3662	0.9501	4000	0.3580	0.9278	0.9310	0.9062	0.9572

Framework versions

• PEFT 0.15.1
• Transformers 4.51.1
• Pytorch 2.5.1+cu121
• Datasets 3.5.0
• Tokenizers 0.21.0