---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- EunsuKim/instruct
- EunsuKim/MATH
model-index:
- name: zephyr-7b-math-case-7
  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-math-case-7

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the EunsuKim/instruct and the EunsuKim/MATH datasets.
It achieves the following results on the evaluation set:
- Loss: 0.0013

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- 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: 0.03
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8719        | 1.0   | 18   | 0.5943          |
| 0.4801        | 2.0   | 36   | 0.2952          |
| 0.2452        | 3.0   | 54   | 0.1275          |
| 0.098         | 4.0   | 72   | 0.0448          |
| 0.0439        | 5.0   | 90   | 0.0259          |
| 0.0306        | 6.0   | 108  | 0.0149          |
| 0.017         | 7.0   | 126  | 0.0068          |
| 0.006         | 8.0   | 144  | 0.0025          |
| 0.0025        | 9.0   | 162  | 0.0014          |
| 0.0012        | 10.0  | 180  | 0.0013          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1