---
license: other
base_model: HuggingFaceM4/idefics-9b
tags:
- generated_from_trainer
model-index:
- name: idefics-9b-dresses-gpt4
  results: []
library_name: peft
---

<!-- 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. -->

# idefics-9b-dresses-gpt4

This model is a fine-tuned version of [HuggingFaceM4/idefics-9b](https://huggingface.co/HuggingFaceM4/idefics-9b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: ['lm_head', 'embed_tokens']
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float16
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0           | 0.03  | 20   | nan             |
| 0.0           | 0.06  | 40   | nan             |
| 0.0           | 0.09  | 60   | nan             |
| 0.0           | 0.12  | 80   | nan             |
| 0.0           | 0.14  | 100  | nan             |
| 0.0           | 0.17  | 120  | nan             |
| 0.0           | 0.2   | 140  | nan             |
| 0.0           | 0.23  | 160  | nan             |
| 0.0           | 0.26  | 180  | nan             |
| 0.0           | 0.29  | 200  | nan             |
| 0.0           | 0.32  | 220  | nan             |
| 0.0           | 0.35  | 240  | nan             |
| 0.0           | 0.38  | 260  | nan             |
| 0.0           | 0.41  | 280  | nan             |
| 0.0           | 0.43  | 300  | nan             |
| 0.0           | 0.46  | 320  | nan             |
| 0.0           | 0.49  | 340  | nan             |
| 0.0           | 0.52  | 360  | nan             |
| 0.0           | 0.55  | 380  | nan             |
| 0.0           | 0.58  | 400  | nan             |
| 0.0           | 0.61  | 420  | nan             |
| 0.0           | 0.64  | 440  | nan             |
| 0.0           | 0.67  | 460  | nan             |
| 0.0           | 0.7   | 480  | nan             |
| 0.0           | 0.72  | 500  | nan             |
| 0.0           | 0.75  | 520  | nan             |
| 0.0           | 0.78  | 540  | nan             |
| 0.0           | 0.81  | 560  | nan             |
| 0.0           | 0.84  | 580  | nan             |
| 0.0           | 0.87  | 600  | nan             |
| 0.0           | 0.9   | 620  | nan             |
| 0.0           | 0.93  | 640  | nan             |
| 0.0           | 0.96  | 660  | nan             |
| 0.0           | 0.99  | 680  | nan             |
| 0.0           | 1.01  | 700  | nan             |
| 0.0           | 1.04  | 720  | nan             |
| 0.0           | 1.07  | 740  | nan             |
| 0.0           | 1.1   | 760  | nan             |
| 0.0           | 1.13  | 780  | nan             |
| 0.0           | 1.16  | 800  | nan             |
| 0.0           | 1.19  | 820  | nan             |
| 0.0           | 1.22  | 840  | nan             |
| 0.0           | 1.25  | 860  | nan             |
| 0.0           | 1.28  | 880  | nan             |
| 0.0           | 1.3   | 900  | nan             |
| 0.0           | 1.33  | 920  | nan             |
| 0.0           | 1.36  | 940  | nan             |
| 0.0           | 1.39  | 960  | nan             |
| 0.0           | 1.42  | 980  | nan             |
| 0.0           | 1.45  | 1000 | nan             |


### Framework versions

- PEFT 0.6.0.dev0
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3