---
license: cc-by-nc-4.0
tags:
- trl
- dpo
- generated_from_trainer
base_model: HuggingFaceTB/SmolLM-360M-Instruct
model-index:
- name: SmolLM-360M-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-360M-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: 0.8873
- Rewards/chosen: 0.0047
- Rewards/rejected: 0.3539
- Rewards/accuracies: 0.0326
- Rewards/margins: -0.3493
- Logps/rejected: -470.7575
- Logps/chosen: -546.0133
- Logits/rejected: 0.3014
- Logits/chosen: 0.6045

## 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5225        | 0.9999 | 3368  | 0.8679          | 0.0092         | 0.3258           | 0.0337             | -0.3166         | -471.0385      | -545.9679    | 0.3212          | 0.6250        |
| 0.4511        | 2.0    | 6737  | 0.8863          | 0.0171         | 0.3649           | 0.0283             | -0.3477         | -470.6477      | -545.8885    | 0.2889          | 0.5939        |
| 0.4453        | 2.9999 | 10105 | 0.8880          | 0.0006         | 0.3516           | 0.0304             | -0.3510         | -470.7807      | -546.0537    | 0.3259          | 0.6291        |
| 0.4439        | 4.0    | 13474 | 0.8894          | 0.0067         | 0.3598           | 0.0228             | -0.3531         | -470.6990      | -545.9932    | 0.2699          | 0.5815        |
| 0.4441        | 4.9999 | 16842 | 0.8881          | 0.0058         | 0.3569           | 0.0293             | -0.3511         | -470.7278      | -546.0020    | 0.2999          | 0.6028        |
| 0.4442        | 5.9991 | 20208 | 0.8873          | 0.0047         | 0.3539           | 0.0326             | -0.3493         | -470.7575      | -546.0133    | 0.3014          | 0.6045        |


### Framework versions

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