peft pytorch mistral alignment-handbook generated_from_trainer dataset:HuggingFaceH4/ultrafeedback_binarized base_model:mistralai/Mistral-7B-v0.1 license:apache-2.0 region:us
---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: r-zephyr-7b-beta-qlora
  results: []
---

# r-zephyr-7b-beta-qlora

The 'r' means replicate. This model is a model replicated by using https://github.com/huggingface/alignment-handbook.

This model is a fine-tuned version on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5232
- Rewards/chosen: -0.9374
- Rewards/rejected: -1.7181
- Rewards/accuracies: 0.7734
- Rewards/margins: 0.7807
- Logps/rejected: -420.1122
- Logps/chosen: -341.2448
- Logits/rejected: 0.6190
- Logits/chosen: 0.6345

## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5917        | 0.21  | 100  | 0.5950          | -0.3904        | -0.7775          | 0.7109             | 0.3872          | -326.0618      | -286.5451    | -1.9790         | -1.9769       |
| 0.5281        | 0.42  | 200  | 0.5492          | -0.8657        | -1.6137          | 0.7617             | 0.7479          | -409.6739      | -334.0814    | -0.2289         | -0.2367       |
| 0.5321        | 0.63  | 300  | 0.5321          | -0.7444        | -1.4427          | 0.7734             | 0.6983          | -392.5731      | -321.9463    | 0.3829          | 0.3741        |
| 0.5149        | 0.84  | 400  | 0.5233          | -0.9570        | -1.7432          | 0.7617             | 0.7862          | -422.6298      | -343.2071    | 0.6479          | 0.6688        |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_amu__r-zephyr-7b-beta-qlora)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |62.70|
|AI2 Reasoning Challenge (25-Shot)|63.05|
|HellaSwag (10-Shot)              |85.38|
|MMLU (5-Shot)                    |63.10|
|TruthfulQA (0-shot)              |46.32|
|Winogrande (5-shot)              |79.32|
|GSM8k (5-shot)                   |39.04|

