---
license: cc-by-nc-4.0
tags:
- trl
- dpo
- generated_from_trainer
base_model: HuggingFaceTB/SmolLM-360M-Instruct
model-index:
- name: SmolLM-1.7B-Instruct-dpo-16k
  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-dpo-16k

This model is a fine-tuned version of [HuggingFaceTB/SmolLM-360M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-360M-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8854
- Rewards/chosen: 0.0056
- Rewards/rejected: 0.3516
- Rewards/accuracies: 0.0326
- Rewards/margins: -0.3460
- Logps/rejected: -470.7809
- Logps/chosen: -546.0043
- Logits/rejected: 0.3165
- Logits/chosen: 0.6158

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2
- num_epochs: 6

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5228        | 0.9999 | 3368  | 0.8697          | 0.0208         | 0.3405           | 0.0348             | -0.3197         | -470.8920      | -545.8519    | 0.3270          | 0.6295        |
| 0.4508        | 2.0    | 6737  | 0.8870          | 0.0130         | 0.3621           | 0.0228             | -0.3491         | -470.6755      | -545.9296    | 0.2662          | 0.5778        |
| 0.4451        | 2.9999 | 10105 | 0.8871          | 0.0057         | 0.3546           | 0.0337             | -0.3489         | -470.7502      | -546.0029    | 0.2855          | 0.5938        |
| 0.4447        | 4.0    | 13474 | 0.8869          | 0.0098         | 0.3588           | 0.0196             | -0.3490         | -470.7085      | -545.9620    | 0.3198          | 0.6222        |
| 0.4446        | 4.9999 | 16842 | 0.8870          | 0.0065         | 0.3551           | 0.0391             | -0.3486         | -470.7452      | -545.9945    | 0.3097          | 0.6124        |
| 0.4448        | 5.9991 | 20208 | 0.8854          | 0.0056         | 0.3516           | 0.0326             | -0.3460         | -470.7809      | -546.0043    | 0.3165          | 0.6158        |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1