---
license: mit
base_model: HuggingFaceH4/zephyr-7b-beta
tags:
- generated_from_trainer
model-index:
- name: non-qa-sft-zephyr-7b-beta-v1
  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. -->

# non-qa-sft-zephyr-7b-beta-v1

This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5768

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3178        | 0.03  | 50   | 1.0767          |
| 0.7765        | 0.07  | 100  | 0.7130          |
| 0.6491        | 0.1   | 150  | 0.6840          |
| 0.6441        | 0.14  | 200  | 0.6829          |
| 0.701         | 0.17  | 250  | 0.6642          |
| 0.6936        | 0.21  | 300  | 0.6427          |
| 0.6538        | 0.24  | 350  | 0.6175          |
| 0.5927        | 0.27  | 400  | 0.6139          |
| 0.6709        | 0.31  | 450  | 0.6129          |
| 0.5961        | 0.34  | 500  | 0.6078          |
| 0.6161        | 0.38  | 550  | 0.5956          |
| 0.5999        | 0.41  | 600  | 0.5938          |
| 0.6248        | 0.44  | 650  | 0.5824          |
| 0.6494        | 0.48  | 700  | 0.5806          |
| 0.6259        | 0.51  | 750  | 0.5767          |
| 0.557         | 0.55  | 800  | 0.5762          |
| 0.6215        | 0.58  | 850  | 0.5777          |
| 0.5986        | 0.62  | 900  | 0.5770          |
| 0.6224        | 0.65  | 950  | 0.5767          |
| 0.6058        | 0.68  | 1000 | 0.5768          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0
- Datasets 2.15.0
- Tokenizers 0.15.0