metadata
base_model: HuggingFaceTB/SmolLM-1.7B
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: SmolLM-1.7B-Instruct-Finetune-LoRA
results: []
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