---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-prometheus_consistent-low-curriculum
  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-7b-dpo-full-prometheus_consistent-low-curriculum

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5227
- Rewards/chosen: -0.6988
- Rewards/rejected: -1.6296
- Rewards/accuracies: 0.7629
- Rewards/margins: 0.9308
- Logps/rejected: -382.0352
- Logps/chosen: -345.4830
- Logits/rejected: 0.7649
- Logits/chosen: -0.3664

## 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: 55
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6619        | 0.1143 | 50   | 0.6465          | -0.0188        | -0.1651          | 0.6940             | 0.1464          | -235.5894      | -277.4793    | -2.4695         | -2.5696       |
| 0.5843        | 0.2286 | 100  | 0.5720          | -0.4443        | -1.0204          | 0.7457             | 0.5761          | -321.1169      | -320.0323    | -1.1914         | -1.3850       |
| 0.5509        | 0.3429 | 150  | 0.5467          | -0.4786        | -1.2647          | 0.7328             | 0.7861          | -345.5482      | -323.4684    | -0.6635         | -1.3552       |
| 0.5275        | 0.4571 | 200  | 0.5396          | -0.5220        | -1.3807          | 0.7716             | 0.8587          | -357.1487      | -327.8021    | -0.0895         | -1.0377       |
| 0.5665        | 0.5714 | 250  | 0.5405          | -1.0842        | -1.9608          | 0.7629             | 0.8766          | -415.1577      | -384.0230    | 1.5254          | 0.2878        |
| 0.5202        | 0.6857 | 300  | 0.5275          | -0.7424        | -1.7347          | 0.7716             | 0.9923          | -392.5496      | -349.8434    | 0.9934          | -0.2192       |
| 0.5261        | 0.8    | 350  | 0.5234          | -0.7613        | -1.7196          | 0.7586             | 0.9584          | -391.0397      | -351.7310    | 0.9008          | -0.2697       |
| 0.5343        | 0.9143 | 400  | 0.5227          | -0.6988        | -1.6296          | 0.7629             | 0.9308          | -382.0352      | -345.4830    | 0.7649          | -0.3664       |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1