---
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-1.7B
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
model-index:
- name: HuggingFaceTB/SmolLM2-1.7B
  results: []
---

<!-- 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. -->

# HuggingFaceTB/SmolLM2-1.7B

This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-1.7B](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7823

## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3348        | 0.0551 | 200  | 1.2704          |
| 1.0411        | 0.1101 | 400  | 1.0435          |
| 1.0483        | 0.1652 | 600  | 0.9694          |
| 0.8801        | 0.2202 | 800  | 0.9227          |
| 0.8996        | 0.2753 | 1000 | 0.8888          |
| 0.8682        | 0.3303 | 1200 | 0.8648          |
| 0.8757        | 0.3854 | 1400 | 0.8468          |
| 0.8441        | 0.4404 | 1600 | 0.8311          |
| 0.8197        | 0.4955 | 1800 | 0.8206          |
| 0.7807        | 0.5505 | 2000 | 0.8090          |
| 0.7757        | 0.6056 | 2200 | 0.8015          |
| 0.7818        | 0.6607 | 2400 | 0.7957          |
| 0.8235        | 0.7157 | 2600 | 0.7915          |
| 0.7854        | 0.7708 | 2800 | 0.7883          |
| 0.7958        | 0.8258 | 3000 | 0.7863          |
| 0.8192        | 0.8809 | 3200 | 0.7829          |
| 0.765         | 0.9359 | 3400 | 0.7824          |
| 0.7939        | 0.9910 | 3600 | 0.7824          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.21.0