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---
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 |