tensorboard safetensors trl sft generated_from_trainer base_model:HuggingFaceH4/zephyr-7b-beta license:mit region:us
---
license: mit
base_model: HuggingFaceH4/zephyr-7b-beta
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: results
  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. -->

# results

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: 0.6622

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5641        | 0.14  | 100  | 1.4610          |
| 1.1695        | 0.28  | 200  | 1.0388          |
| 1.0319        | 0.42  | 300  | 0.9440          |
| 0.905         | 0.56  | 400  | 0.8829          |
| 0.8655        | 0.7   | 500  | 0.8225          |
| 0.8329        | 0.85  | 600  | 0.8042          |
| 0.85          | 0.99  | 700  | 0.7728          |
| 0.7348        | 1.13  | 800  | 0.7426          |
| 0.6723        | 1.27  | 900  | 0.7197          |
| 0.6791        | 1.41  | 1000 | 0.6933          |
| 0.6576        | 1.55  | 1100 | 0.6864          |
| 0.6863        | 1.69  | 1200 | 0.6731          |
| 0.6328        | 1.83  | 1300 | 0.6652          |
| 0.6264        | 1.97  | 1400 | 0.6622          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
