gimarchetti's picture
End of training
f47429a verified
metadata
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: []

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

This model is a fine-tuned version of 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