---
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-full
  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-full

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: 0.5465
- Rewards/chosen: -0.0518
- Rewards/rejected: -0.7661
- Rewards/accuracies: 0.7170
- Rewards/margins: 0.7143
- Logps/rejected: -450.2018
- Logps/chosen: -588.7877
- Logits/rejected: -4.9602
- Logits/chosen: -5.2468

## 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: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6549        | 0.26  | 1000  | 0.6037          | -0.1205        | -0.4850          | 0.6550             | 0.3644          | -447.3903      | -589.4750    | -4.7410         | -5.0341       |
| 0.5349        | 0.52  | 2000  | 0.5779          | -0.0126        | -0.5080          | 0.6770             | 0.4955          | -447.6208      | -588.3951    | -4.8645         | -5.1463       |
| 0.6029        | 0.77  | 3000  | 0.5657          | 0.0902         | -0.4636          | 0.6900             | 0.5538          | -447.1767      | -587.3674    | -5.0016         | -5.2911       |
| 0.5273        | 1.03  | 4000  | 0.5596          | 0.0496         | -0.5449          | 0.7040             | 0.5944          | -447.9891      | -587.7738    | -4.9972         | -5.2892       |
| 0.5           | 1.29  | 5000  | 0.5557          | 0.0585         | -0.6110          | 0.7050             | 0.6695          | -448.6505      | -587.6843    | -5.0108         | -5.3047       |
| 0.5056        | 1.55  | 6000  | 0.5499          | 0.0054         | -0.6719          | 0.7130             | 0.6773          | -449.2598      | -588.2154    | -4.9988         | -5.2907       |
| 0.4608        | 1.81  | 7000  | 0.5500          | -0.0376        | -0.7494          | 0.7030             | 0.7118          | -450.0341      | -588.6455    | -5.0549         | -5.3406       |
| 0.426         | 2.07  | 8000  | 0.5472          | -0.0106        | -0.7021          | 0.7100             | 0.6916          | -449.5617      | -588.3751    | -4.9750         | -5.2626       |
| 0.3875        | 2.32  | 9000  | 0.5464          | -0.0011        | -0.7171          | 0.7140             | 0.7159          | -449.7113      | -588.2810    | -4.9935         | -5.2796       |
| 0.397         | 2.58  | 10000 | 0.5462          | -0.0391        | -0.7566          | 0.7190             | 0.7175          | -450.1064      | -588.6602    | -4.9737         | -5.2618       |
| 0.4486        | 2.84  | 11000 | 0.5459          | -0.0493        | -0.7667          | 0.7110             | 0.7174          | -450.2074      | -588.7629    | -4.9569         | -5.2441       |


### Framework versions

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