---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: zephyr-7b-sft-full
  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-full

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9934

## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 256
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9681        | 0.1845 | 100  | 0.9788          |
| 0.9962        | 0.3690 | 200  | 1.0030          |
| 0.9917        | 0.5535 | 300  | 1.0008          |
| 0.9652        | 0.7380 | 400  | 0.9939          |
| 0.9666        | 0.9225 | 500  | 0.9816          |
| 0.7366        | 1.1070 | 600  | 0.9852          |
| 0.7228        | 1.2915 | 700  | 0.9835          |
| 0.7319        | 1.4760 | 800  | 0.9644          |
| 0.7177        | 1.6605 | 900  | 0.9529          |
| 0.7095        | 1.8450 | 1000 | 0.9394          |
| 0.4465        | 2.0295 | 1100 | 0.9917          |
| 0.4341        | 2.2140 | 1200 | 0.9979          |
| 0.432         | 2.3985 | 1300 | 0.9954          |
| 0.4301        | 2.5830 | 1400 | 0.9943          |
| 0.4361        | 2.7675 | 1500 | 0.9931          |
| 0.4256        | 2.9520 | 1600 | 0.9934          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.2.2+rocm5.7
- Datasets 3.2.0
- Tokenizers 0.20.3