---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- data/uf_rlced_conifer
model-index:
- name: zephyr-7b-uf-rlced-conifer-dpo-2e
  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-uf-rlced-conifer-dpo-2e

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 data/uf_rlced_conifer dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2466
- Rewards/chosen: -4.8588
- Rewards/rejected: -13.2530
- Rewards/accuracies: 0.8966
- Rewards/margins: 8.3941
- Logps/rejected: -1735.4203
- Logps/chosen: -870.4680
- Logits/rejected: 4.3075
- Logits/chosen: 1.8380

## 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: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1587        | 1.3879 | 1000 | 0.2471          | -3.9472        | -12.0338         | 0.8910             | 8.0866          | -1613.5016     | -779.3055    | 4.5606          | 2.4398        |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1