---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
base_model: BEE-spoke-data/smol_llama-220M-openhermes
model-index:
- name: zephyr-220m-sft-full
  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-220m-sft-full

This model is a fine-tuned version of [BEE-spoke-data/smol_llama-220M-openhermes](https://huggingface.co/BEE-spoke-data/smol_llama-220M-openhermes) on the Ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6579

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6447        | 1.0   | 1624 | 1.6579          |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

https://wandb.ai/amazingvince/huggingface/runs/5rffzk3x/workspace?workspace=user-amazingvince
# [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_BEE-spoke-data__zephyr-220m-sft-full)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |29.33|
|AI2 Reasoning Challenge (25-Shot)|25.26|
|HellaSwag (10-Shot)              |29.03|
|MMLU (5-Shot)                    |26.45|
|TruthfulQA (0-shot)              |43.23|
|Winogrande (5-shot)              |51.62|
|GSM8k (5-shot)                   | 0.38|