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

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: 1.0730

## 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: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.171         | 0.1119 | 50   | 1.2339          |
| 1.2051        | 0.2237 | 100  | 1.1744          |
| 1.1372        | 0.3356 | 150  | 1.1323          |
| 1.1046        | 0.4474 | 200  | 1.1095          |
| 1.0673        | 0.5593 | 250  | 1.0877          |
| 1.0713        | 0.6711 | 300  | 1.0761          |
| 1.0824        | 0.7830 | 350  | 1.0611          |
| 1.0358        | 0.8949 | 400  | 1.0511          |
| 1.0288        | 1.0067 | 450  | 1.0389          |
| 0.9158        | 1.1186 | 500  | 1.0443          |
| 0.9199        | 1.2304 | 550  | 1.0382          |
| 0.9032        | 1.3423 | 600  | 1.0339          |
| 0.8834        | 1.4541 | 650  | 1.0292          |
| 0.9048        | 1.5660 | 700  | 1.0271          |
| 0.9101        | 1.6779 | 750  | 1.0193          |
| 0.8928        | 1.7897 | 800  | 1.0164          |
| 0.9032        | 1.9016 | 850  | 1.0124          |
| 0.8649        | 2.0134 | 900  | 1.0234          |
| 0.7615        | 2.1253 | 950  | 1.0433          |
| 0.7588        | 2.2371 | 1000 | 1.0366          |
| 0.7759        | 2.3490 | 1050 | 1.0331          |
| 0.7696        | 2.4609 | 1100 | 1.0349          |
| 0.7587        | 2.5727 | 1150 | 1.0324          |
| 0.7532        | 2.6846 | 1200 | 1.0309          |
| 0.7702        | 2.7964 | 1250 | 1.0287          |
| 0.7648        | 2.9083 | 1300 | 1.0275          |
| 0.7452        | 3.0201 | 1350 | 1.0529          |
| 0.6471        | 3.1320 | 1400 | 1.0683          |
| 0.665         | 3.2438 | 1450 | 1.0727          |
| 0.6563        | 3.3557 | 1500 | 1.0713          |
| 0.6499        | 3.4676 | 1550 | 1.0721          |
| 0.6538        | 3.5794 | 1600 | 1.0741          |
| 0.6437        | 3.6913 | 1650 | 1.0740          |
| 0.6486        | 3.8031 | 1700 | 1.0734          |
| 0.66          | 3.9150 | 1750 | 1.0730          |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1