---
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-9e-07-0.86-linear-2.0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zephyr-7b-align-scan-9e-07-0.86-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: 1.2207
- Rewards/chosen: 0.7526
- Rewards/rejected: -1.3224
- Rewards/accuracies: 0.3294
- Rewards/margins: 2.0750
- Logps/rejected: -82.6661
- Logps/chosen: -73.6161
- Logits/rejected: -2.6026
- Logits/chosen: -2.6190

## 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: 9e-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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.9734        | 0.3484 | 100  | 0.9203          | 2.0652         | 1.3351           | 0.3294             | 0.7302          | -79.5760       | -72.0898     | -2.5695         | -2.5853       |
| 0.9883        | 0.6969 | 200  | 1.0967          | 2.4271         | 1.1885           | 0.3373             | 1.2386          | -79.7464       | -71.6691     | -2.5708         | -2.5875       |
| 0.4215        | 1.0453 | 300  | 1.1234          | 3.0876         | 1.7905           | 0.3313             | 1.2970          | -79.0463       | -70.9010     | -2.6403         | -2.6560       |
| 0.393         | 1.3937 | 400  | 1.2234          | -0.1343        | -1.8934          | 0.3234             | 1.7591          | -83.3299       | -74.6474     | -2.6093         | -2.6250       |
| 0.3986        | 1.7422 | 500  | 1.2247          | 0.1937         | -1.8484          | 0.3214             | 2.0420          | -83.2776       | -74.2660     | -2.5909         | -2.6070       |


### Framework versions

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