---
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-3e-07-0.62-polynomial-3.0
  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-3e-07-0.62-polynomial-3.0

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: 0.8726
- Rewards/chosen: -0.1874
- Rewards/rejected: -1.8304
- Rewards/accuracies: 0.375
- Rewards/margins: 1.6430
- Logps/rejected: -84.0806
- Logps/chosen: -74.7935
- Logits/rejected: -2.6285
- Logits/chosen: -2.6453

## 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: 3e-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: polynomial
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6629        | 0.3484 | 100  | 0.6374          | 0.7586         | 0.3997           | 0.3452             | 0.3589          | -80.4837       | -73.2678     | -2.5455         | -2.5615       |
| 0.7044        | 0.6969 | 200  | 0.6785          | 0.6115         | 0.1187           | 0.3353             | 0.4927          | -80.9369       | -73.5050     | -2.5325         | -2.5487       |
| 0.3945        | 1.0453 | 300  | 0.6975          | 0.7667         | 0.1071           | 0.3552             | 0.6597          | -80.9557       | -73.2546     | -2.5596         | -2.5753       |
| 0.3859        | 1.3937 | 400  | 0.7396          | 1.4671         | 0.5658           | 0.3571             | 0.9013          | -80.2158       | -72.1250     | -2.5834         | -2.5995       |
| 0.3893        | 1.7422 | 500  | 0.7904          | -0.4771        | -1.4060          | 0.3492             | 0.9290          | -83.3962       | -75.2607     | -2.6499         | -2.6659       |
| 0.3749        | 2.0906 | 600  | 0.8125          | 0.5611         | -0.4847          | 0.3631             | 1.0458          | -81.9100       | -73.5862     | -2.6159         | -2.6321       |
| 0.3662        | 2.4390 | 700  | 0.8412          | -0.6104        | -2.0869          | 0.3651             | 1.4765          | -84.4944       | -75.4757     | -2.5941         | -2.6112       |
| 0.3615        | 2.7875 | 800  | 0.8766          | -0.9523        | -2.5666          | 0.3611             | 1.6143          | -85.2680       | -76.0272     | -2.6367         | -2.6538       |


### Framework versions

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