---
library_name: transformers
license: apache-2.0
base_model: bespokelabs/Bespoke-Stratos-7B
tags:
- llama-factory
- full
- trl
- dpo
- llama-factory
- generated_from_trainer
model-index:
- name: dpo_from_multiple_samples_shortest_numina_aime
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# dpo_from_multiple_samples_shortest_numina_aime

This model is a fine-tuned version of [bespokelabs/Bespoke-Stratos-7B](https://huggingface.co/bespokelabs/Bespoke-Stratos-7B) on the mlfoundations-dev/dpo_from_multiple_samples_shortest_numina_aime dataset.
It achieves the following results on the evaluation set:
- Loss: 4.5934
- Rewards/chosen: -7.6229
- Rewards/rejected: -8.1168
- Rewards/accuracies: 0.5859
- Rewards/margins: 0.4940
- Logps/chosen: -0.7623
- Logps/rejected: -0.8117
- Logits/chosen: -0.6184
- Logits/rejected: -0.4483

## 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: 8e-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.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: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logits/chosen | Logits/rejected |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:|
| 4.3711        | 0.96  | 18   | 4.5934          | -7.6229        | -8.1168          | 0.5859             | 0.4940          | -0.7623      | -0.8117        | -0.6184       | -0.4483         |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3