fine_tune_output

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 4.2902

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 100

Training results

Training Loss	Epoch	Step	Validation Loss
5.061	7.2727	10	3.1055
3.6905	14.5455	20	2.6699
2.4714	21.8182	30	1.8229
0.9142	29.0909	40	1.8090
0.0188	36.3636	50	3.1047
0.0544	43.6364	60	3.8352
0.0316	50.9091	70	3.7350
0.0116	58.1818	80	3.7428
0.0005	65.4545	90	4.4955
0.0001	72.7273	100	4.2902

Framework versions

• PEFT 0.10.0
• Transformers 4.46.2
• Pytorch 2.5.1+cu124
• Datasets 3.1.0
• Tokenizers 0.20.3