---
license: apache-2.0
base_model: HachiML/Mists-7B-v01-simple-projector-trained
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Mists-7B-v01-simpleQA
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/siseikatu8/huggingface/runs/ttzci7jp)
# Mists-7B-v01-simpleQA

This model is a fine-tuned version of [HachiML/Mists-7B-v01-simple-projector-trained](https://huggingface.co/HachiML/Mists-7B-v01-simple-projector-trained) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0972

## 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: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1811        | 0.0888 | 50   | 5.1410          |
| 1.2662        | 0.1776 | 100  | 4.0209          |
| 0.5676        | 0.2664 | 150  | 3.6247          |
| 0.6122        | 0.3552 | 200  | 2.5723          |
| 0.3855        | 0.4440 | 250  | 1.8618          |
| 0.5471        | 0.5329 | 300  | 1.5969          |
| 0.5238        | 0.6217 | 350  | 0.9045          |
| 0.3799        | 0.7105 | 400  | 0.5475          |
| 0.2406        | 0.7993 | 450  | 0.1614          |
| 0.1381        | 0.8881 | 500  | 0.1055          |
| 0.0992        | 0.9769 | 550  | 0.0972          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.0.1
- Datasets 2.20.0
- Tokenizers 0.19.1