---
license: cc-by-nc-4.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: HuggingFaceTB/SmolLM-1.7B-Instruct
datasets:
- generator
model-index:
- name: SmolLM_1_7B_Instruct_qlora_nf4
  results: []
language:
- en
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# SmolLM_1_7B_Instruct_qlora_nf4

This model is a fine-tuned version of [HuggingFaceTB/SmolLM-1.7B-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-1.7B-Instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6524

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.0516        | 0.9756 | 10   | 1.8985          |
| 1.8456        | 1.9512 | 20   | 1.7876          |
| 1.7672        | 2.9268 | 30   | 1.7327          |
| 1.712         | 4.0    | 41   | 1.6967          |
| 1.6874        | 4.9756 | 51   | 1.6761          |
| 1.6643        | 5.9512 | 61   | 1.6636          |
| 1.6426        | 6.9268 | 71   | 1.6565          |
| 1.6388        | 8.0    | 82   | 1.6530          |
| 1.6387        | 8.9756 | 92   | 1.6524          |
| 1.6343        | 9.7561 | 100  | 1.6524          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.19.1