---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b
  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

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/alignment-handbook/zephyr-7b-sft-qlora) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6906
- Rewards/chosen: -0.3413
- Rewards/rejected: -0.5652
- Rewards/accuracies: 0.3631
- Rewards/margins: 0.2239
- Logps/rejected: -131.9189
- Logps/chosen: -103.0295
- Logits/rejected: -0.1381
- Logits/chosen: -0.2453
- Use Label: 15879.8574
- Pred Label: 4192.1431

## 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: 4
- gradient_accumulation_steps: 4
- 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: 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 | Use Label  | Pred Label |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:----------:|:----------:|
| 0.6818        | 0.1   | 100  | 0.6814          | -0.0056        | -0.0496          | 0.3393             | 0.0440          | -80.3582       | -69.4632     | -2.0664         | -2.0975       | 1833.4603  | 22.5397    |
| 0.6818        | 0.21  | 200  | 0.6861          | -0.1358        | -0.2381          | 0.3373             | 0.1023          | -99.2068       | -82.4782     | -1.9938         | -2.0215       | 3701.2063  | 258.7936   |
| 0.6848        | 0.31  | 300  | 0.6877          | -0.2068        | -0.3388          | 0.3413             | 0.1320          | -109.2766      | -89.5763     | -1.8828         | -1.9157       | 5437.8730  | 626.1270   |
| 0.6857        | 0.42  | 400  | 0.6885          | -0.1802        | -0.3299          | 0.3532             | 0.1497          | -108.3913      | -86.9237     | -1.4031         | -1.4529       | 7112.4443  | 1055.5555  |
| 0.6894        | 0.52  | 500  | 0.6892          | -0.2862        | -0.4559          | 0.3552             | 0.1697          | -120.9922      | -97.5203     | -0.5997         | -0.6889       | 8741.4287  | 1530.5714  |
| 0.6881        | 0.63  | 600  | 0.6918          | -0.3826        | -0.6059          | 0.3532             | 0.2233          | -135.9845      | -107.1618    | -0.2548         | -0.3579       | 10293.6826 | 2082.3174  |
| 0.6913        | 0.73  | 700  | 0.6899          | -0.3542        | -0.5787          | 0.3671             | 0.2244          | -133.2637      | -104.3247    | -0.2462         | -0.3470       | 11806.4766 | 2673.5239  |
| 0.6893        | 0.84  | 800  | 0.6904          | -0.3443        | -0.5684          | 0.3631             | 0.2241          | -132.2416      | -103.3355    | -0.1293         | -0.2367       | 13331.9043 | 3252.0952  |
| 0.689         | 0.94  | 900  | 0.6907          | -0.3413        | -0.5651          | 0.3631             | 0.2238          | -131.9111      | -103.0301    | -0.1367         | -0.2437       | 14866.4766 | 3821.5239  |


### Framework versions

- PEFT 0.7.1
- Transformers 4.38.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2