---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- SFT
- WeniGPT
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- generator
model-index:
- name: WeniGPT-Agents-Mistral-1.0.11-SFT
  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. -->

# WeniGPT-Agents-Mistral-1.0.11-SFT

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1287

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 330

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0466        | 0.5357 | 30   | 1.1547          |
| 0.8783        | 1.0714 | 60   | 1.1288          |
| 0.6778        | 1.6071 | 90   | 1.1287          |
| 0.4609        | 2.1429 | 120  | 1.1453          |
| 0.3946        | 2.6786 | 150  | 1.1766          |
| 0.2669        | 3.2143 | 180  | 1.2127          |
| 0.2871        | 3.75   | 210  | 1.2313          |
| 0.1831        | 4.2857 | 240  | 1.2560          |
| 0.2145        | 4.8214 | 270  | 1.2665          |
| 0.167         | 5.3571 | 300  | 1.2968          |
| 0.1569        | 5.8929 | 330  | 1.2957          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.19.1