---
license: apache-2.0
base_model: argilla/zephyr-7b-spin-iter2-v0
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-spin-iter3-v0
  results: []
datasets:
- argilla/10k_prompts_SPIN_iter3_zephyr_top
- argilla/10k_prompts_SPIN_iter2_zephyr_top
- DIBT/10k_prompts_ranked
---

<!-- 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-spin-iter3-v0

> A model matching the results of SPIN with very little data (30x less), carefully curated by the amazing [Data Is Better Together community](https://huggingface.co./DIBT)

<div>
    <img src="https://cdn-uploads.huggingface.co/production/uploads/60420dccc15e823a685f2b03/aEzpD6gvn0xOrN2rNzpZI.webp">
</div>


<p align="center">
  <a href="https://github.com/argilla-io/distilabel">
    <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
  </a>
</p>

This model is a fine-tuned version of [argilla/zephyr-7b-spin-iter2-v0](https://huggingface.co./argilla/zephyr-7b-spin-iter2-v0) on the
[argilla/10k_prompts_SPIN_iter3_zephyr_top](https://huggingface.co./datasets/argilla/10k_prompts_SPIN_iter3_zephyr_top) and the 
[argilla/10k_prompts_SPIN_iter2_zephyr_top](https://huggingface.co./datasets/argilla/10k_prompts_SPIN_iter2_zephyr_top) dataset.

Check [this repo](https://github.com/argilla-io/distilabel-spin-dibt) for full reproducible code using the original SPIN implementation and distilabel.

If you want to contribute to high quality datasets like this, contribute to the [DIBT prompt collective initiative](https://huggingface.co./spaces/DIBT/prompt-collective-dashboard).


## MT-Bench results

| Model                   | 1st Turn Score | 2nd Turn Score | Average Score | SPIN paper Score |
|-------------------------|----------------|----------------|---------------|------------------|
| zephyr-7b-sft-full      | 6.6625         | 6.0250         | 6.34375       |  5.94            |
| zephyr-7b-spin-iter0-v0 | 6.64375        | 6.1750         | 6.409375      |  6.46            |
| zephyr-7b-spin-iter1-v0 | 6.90625        | 6.3000         | 6.603125      |  6.65            |
| zephyr-7b-spin-iter2-v0 | **7.1375**     | 6.3125         | 6.725000      |  6.78            |
| zephyr-7b-spin-iter3-v0 | 7.09375        | **6.4500**     | **6.771875**  |  -               |



## 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: 1e-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: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:|
| 0.2928        | 0.49  | 25   | 0.3951          | -2.6212      | -20.3268          | 0.9062             | 17.7056         | -700.5638       | -278.0876  | -2.8098          | -2.8090     |
| 0.1487        | 0.97  | 50   | 0.1319          | -2.9077      | -29.1459          | 0.9375             | 26.2382         | -702.3276       | -278.1449  | -2.8218          | -2.8066     |
| 0.006         | 1.46  | 75   | 0.1269          | -2.6037      | -29.1519          | 0.9583             | 26.5482         | -702.3289       | -278.0841  | -2.8175          | -2.8037     |
| 0.0086        | 1.94  | 100  | 0.1099          | -2.9181      | -29.6970          | 0.9271             | 26.7789         | -702.4378       | -278.1470  | -2.8177          | -2.8051     |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2