transformers tensorboard safetensors mistral text-generation alignment-handbook generated_from_trainer trl dpo conversational dataset:HuggingFaceH4/ultrafeedback_binarized base_model:alignment-handbook/zephyr-7b-sft-full license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-full-repnew
  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-repnew

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 HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5036
- Rewards/chosen: -1.1057
- Rewards/rejected: -2.0459
- Rewards/accuracies: 0.7698
- Rewards/margins: 0.9402
- Logps/rejected: -466.3643
- Logps/chosen: -394.6778
- Logits/rejected: 0.8720
- Logits/chosen: 0.0385

## 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: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.5666        | 0.21  | 100  | -1.6453       | -1.5540         | -378.9401    | -411.0335      | 0.5780          | 0.7282             | -0.9484        | 0.5442          | -1.4926          |
| 0.5107        | 0.42  | 200  | -0.1291       | 0.3999          | -386.8341    | -445.9254      | 0.5233          | 0.7480             | -1.0273        | 0.8142          | -1.8415          |
| 0.5036        | 0.63  | 300  | -0.0425       | 0.7446          | -387.1995    | -449.6839      | 0.5109          | 0.7599             | -1.0310        | 0.8481          | -1.8791          |
| 0.485         | 0.84  | 400  | 0.0635        | 0.9022          | -397.1799    | -468.7184      | 0.5047          | 0.7639             | -1.1308        | 0.9387          | -2.0694          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2
