---
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/MATH
model-index:
- name: zephyr-7b-math-train-test
  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-train-test

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/MATH dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0130

## 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.746         | 1.0   | 10   | 0.6231          |
| 0.5258        | 2.0   | 20   | 0.3843          |
| 0.3183        | 3.0   | 30   | 0.1999          |
| 0.16          | 4.0   | 40   | 0.0864          |
| 0.0811        | 5.0   | 50   | 0.0496          |
| 0.0502        | 6.0   | 60   | 0.0345          |
| 0.035         | 7.0   | 70   | 0.0254          |
| 0.0241        | 8.0   | 80   | 0.0185          |
| 0.0165        | 9.0   | 90   | 0.0142          |
| 0.0129        | 10.0  | 100  | 0.0130          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1