---
license: mit
base_model: HuggingFaceH4/zephyr-7b-beta
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-sft-lora-accum4-lr5e_5-dpo
  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-sft-lora-accum4-lr5e_5-dpo

This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5041

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- 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
- num_epochs: 30.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5276        | 0.55  | 13   | 1.4329          |
| 1.352         | 1.57  | 27   | 1.2406          |
| 1.1329        | 2.55  | 40   | 1.0909          |
| 1.0628        | 3.57  | 54   | 1.0299          |
| 1.0022        | 4.55  | 67   | 0.9812          |
| 0.957         | 5.57  | 81   | 0.9445          |
| 0.9148        | 6.55  | 94   | 0.8948          |
| 0.8443        | 7.57  | 108  | 0.8432          |
| 0.7645        | 8.55  | 121  | 0.7847          |
| 0.6952        | 9.57  | 135  | 0.7192          |
| 0.639         | 10.55 | 148  | 0.6671          |
| 0.5683        | 11.57 | 162  | 0.6112          |
| 0.5223        | 12.55 | 175  | 0.5777          |
| 0.4958        | 13.57 | 189  | 0.5592          |
| 0.4592        | 14.55 | 202  | 0.5381          |
| 0.4602        | 15.57 | 216  | 0.5100          |
| 0.4486        | 16.55 | 229  | 0.5117          |
| 0.4274        | 17.57 | 243  | 0.5084          |
| 0.4239        | 18.55 | 256  | 0.4909          |
| 0.4055        | 19.57 | 270  | 0.5006          |
| 0.3931        | 20.55 | 283  | 0.4959          |
| 0.3986        | 21.57 | 297  | 0.4853          |
| 0.3977        | 22.55 | 310  | 0.4859          |
| 0.3936        | 23.57 | 324  | 0.4974          |
| 0.3821        | 24.55 | 337  | 0.4952          |
| 0.3877        | 25.57 | 351  | 0.4949          |
| 0.3681        | 26.55 | 364  | 0.4866          |
| 0.3681        | 27.57 | 378  | 0.4926          |
| 0.371         | 28.55 | 391  | 0.4817          |
| 0.3604        | 29.57 | 405  | 0.4923          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1