---
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:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-align-scan-2e-07-0.5-linear-2.0
  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-align-scan-2e-07-0.5-linear-2.0

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: 0.6464
- Rewards/chosen: 0.4833
- Rewards/rejected: -0.1353
- Rewards/accuracies: 0.3710
- Rewards/margins: 0.6186
- Logps/rejected: -81.3989
- Logps/chosen: -73.5245
- Logits/rejected: -2.5552
- Logits/chosen: -2.5716

## 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: 2e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6562        | 0.3484 | 100  | 0.6328          | 0.6802         | 0.3841           | 0.3552             | 0.2961          | -80.3602       | -73.1308     | -2.5405         | -2.5565       |
| 0.6601        | 0.6969 | 200  | 0.6410          | 0.2989         | -0.0897          | 0.3452             | 0.3887          | -81.3078       | -73.8934     | -2.5169         | -2.5332       |
| 0.4195        | 1.0453 | 300  | 0.6371          | 0.6242         | 0.1593           | 0.3532             | 0.4648          | -80.8097       | -73.2429     | -2.5193         | -2.5354       |
| 0.3956        | 1.3937 | 400  | 0.6460          | 0.4324         | -0.1472          | 0.3631             | 0.5796          | -81.4227       | -73.6264     | -2.5378         | -2.5541       |
| 0.3945        | 1.7422 | 500  | 0.6465          | 0.3072         | -0.2969          | 0.3710             | 0.6040          | -81.7221       | -73.8769     | -2.5543         | -2.5709       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1