---
license: apache-2.0
base_model: HuggingFaceM4/idefics2-8b
tags:
- generated_from_trainer
model-index:
- name: gm-lora-bfloat16-idefics2-8b-xrayvqa-finetuned-medir2
  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. -->

# gm-lora-bfloat16-idefics2-8b-xrayvqa-finetuned-medir2

This model is a fine-tuned version of [HuggingFaceM4/idefics2-8b](https://huggingface.co/HuggingFaceM4/idefics2-8b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6349

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1259        | 0.0764 | 50   | 1.4468          |
| 1.2502        | 0.1529 | 100  | 1.4544          |
| 1.2599        | 0.2293 | 150  | 1.4605          |
| 1.1477        | 0.3058 | 200  | 1.4844          |
| 1.1041        | 0.3822 | 250  | 1.4835          |
| 1.0958        | 0.4586 | 300  | 1.4724          |
| 1.0975        | 0.5351 | 350  | 1.4800          |
| 1.133         | 0.6115 | 400  | 1.4656          |
| 1.1785        | 0.6880 | 450  | 1.4458          |
| 1.3751        | 0.7644 | 500  | 1.4227          |
| 1.3751        | 0.8409 | 550  | 1.4187          |
| 1.3983        | 0.9173 | 600  | 1.4158          |
| 1.4147        | 0.9937 | 650  | 1.4073          |
| 0.9615        | 1.0702 | 700  | 1.4901          |
| 0.9026        | 1.1466 | 750  | 1.5204          |
| 0.8919        | 1.2231 | 800  | 1.4997          |
| 0.917         | 1.2995 | 850  | 1.4994          |
| 0.9149        | 1.3759 | 900  | 1.4998          |
| 0.9342        | 1.4524 | 950  | 1.4971          |
| 0.9363        | 1.5288 | 1000 | 1.5039          |
| 0.9087        | 1.6053 | 1050 | 1.4907          |
| 0.9272        | 1.6817 | 1100 | 1.4920          |
| 0.9195        | 1.7581 | 1150 | 1.4955          |
| 0.9488        | 1.8346 | 1200 | 1.4900          |
| 0.9209        | 1.9110 | 1250 | 1.4887          |
| 0.9463        | 1.9875 | 1300 | 1.4891          |
| 0.7123        | 2.0639 | 1350 | 1.6077          |
| 0.646         | 2.1403 | 1400 | 1.6182          |
| 0.6405        | 2.2168 | 1450 | 1.6390          |
| 0.6481        | 2.2932 | 1500 | 1.6198          |
| 0.6372        | 2.3697 | 1550 | 1.6340          |
| 0.6618        | 2.4461 | 1600 | 1.6311          |
| 0.6499        | 2.5226 | 1650 | 1.6277          |
| 0.6471        | 2.5990 | 1700 | 1.6344          |
| 0.6554        | 2.6754 | 1750 | 1.6303          |
| 0.6475        | 2.7519 | 1800 | 1.6333          |
| 0.641         | 2.8283 | 1850 | 1.6315          |
| 0.6274        | 2.9048 | 1900 | 1.6343          |
| 0.6309        | 2.9812 | 1950 | 1.6349          |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.0.1
- Datasets 2.19.1
- Tokenizers 0.19.1