---
license: apache-2.0
base_model: amazingvince/zephyr-smol_llama-100m-sft-full
tags:
- generated_from_trainer
model-index:
- name: zephyr-smol_llama-100m-dpo-1-epoch
  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. -->

# zephyr-smol_llama-100m-dpo-1-epoch

This model is a fine-tuned version of [amazingvince/zephyr-smol_llama-100m-sft-full](https://huggingface.co/amazingvince/zephyr-smol_llama-100m-sft-full) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5661
- Rewards/chosen: 0.0614
- Rewards/rejected: -0.4791
- Rewards/accuracies: 0.6810
- Rewards/margins: 0.5405
- Logps/rejected: -447.3311
- Logps/chosen: -587.6553
- Logits/rejected: -4.9351
- Logits/chosen: -5.2302

## 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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6597        | 0.26  | 1000 | 0.5887          | -0.0788        | -0.5504          | 0.6700             | 0.4715          | -448.0441      | -589.0577    | -4.7945         | -5.0906       |
| 0.5306        | 0.52  | 2000 | 0.5740          | 0.0053         | -0.5021          | 0.6840             | 0.5074          | -447.5612      | -588.2166    | -4.8585         | -5.1486       |
| 0.6036        | 0.77  | 3000 | 0.5676          | 0.0550         | -0.4785          | 0.6890             | 0.5335          | -447.3253      | -587.7193    | -4.9388         | -5.2343       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1