SmolLM-1.7B-Instruct-Finetune-LoRA

This model is a fine-tuned version of HuggingFaceTB/SmolLM-1.7B on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 0.9799

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: 8
• eval_batch_size: 8
• seed: 2503
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• total_eval_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.6526	0.6173	25	1.5373
1.3791	1.2346	50	1.1969
1.1244	1.8519	75	1.0547
1.0282	2.4691	100	1.0055
1.0063	3.0864	125	0.9852
0.9864	3.7037	150	0.9799

Framework versions

• PEFT 0.12.0
• Transformers 4.43.3
• Pytorch 2.4.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1