---
library_name: peft
base_model: HuggingFaceTB/smollm2-1.7B-8k-mix7-ep2-v2
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: smollm2-1.7B-8k-mix7-ep2-v2-qlora-r16-a16-lr3e4-mix1-dpo
  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. -->

# smollm2-1.7B-8k-mix7-ep2-v2-qlora-r16-a16-lr3e4-mix1-dpo

This model is a fine-tuned version of [gabrielmbmb/smollm2-1.7B-8k-mix7-ep2-v2-qlora-r16-a16-lr3e4-mix1](https://huggingface.co/gabrielmbmb/smollm2-1.7B-8k-mix7-ep2-v2-qlora-r16-a16-lr3e4-mix1) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5156
- Rewards/chosen: -4.3948
- Rewards/rejected: -5.4305
- Rewards/accuracies: 0.7656
- Rewards/margins: 1.0357
- Logps/rejected: -849.2994
- Logps/chosen: -752.2209
- Logits/rejected: -1.2614
- Logits/chosen: -1.2341

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5629        | 0.2093 | 100  | 0.5765          | -2.2363        | -2.7515          | 0.7227             | 0.5152          | -581.3958      | -536.3666    | -1.6836         | -1.6572       |
| 0.5499        | 0.4186 | 200  | 0.5310          | -3.6681        | -4.4704          | 0.7734             | 0.8022          | -753.2846      | -679.5535    | -0.8209         | -0.8334       |
| 0.511         | 0.6279 | 300  | 0.5225          | -4.8153        | -5.7685          | 0.7695             | 0.9532          | -883.0991      | -794.2732    | -1.1394         | -1.1157       |
| 0.508         | 0.8373 | 400  | 0.5157          | -4.3456        | -5.3593          | 0.7695             | 1.0137          | -842.1772      | -747.2964    | -1.2109         | -1.1871       |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.0
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1