---
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-test-half
  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-test-half

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: 0.0186

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.969         | 1.0   | 3    | 1.2659          |
| 1.0058        | 2.0   | 6    | 0.7385          |
| 1.0058        | 3.0   | 9    | 0.4851          |
| 0.6526        | 4.0   | 12   | 0.3110          |
| 0.3241        | 5.0   | 15   | 0.1611          |
| 0.3241        | 6.0   | 18   | 0.0703          |
| 0.1058        | 7.0   | 21   | 0.0349          |
| 0.1058        | 8.0   | 24   | 0.0240          |
| 0.033         | 9.0   | 27   | 0.0196          |
| 0.0202        | 10.0  | 30   | 0.0186          |


### Framework versions

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