metadata

license: apache-2.0
base_model: jordyvl/vit-base_rvl-cdip
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: vit-base_rvl_cdip-N1K_ce_128
    results: []

vit-base_rvl_cdip-N1K_ce_128

This model is a fine-tuned version of jordyvl/vit-base_rvl-cdip on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4776
Accuracy: 0.8912
Brier Loss: 0.1798
Nll: 0.9844
F1 Micro: 0.8912
F1 Macro: 0.8915
Ece: 0.0768
Aurc: 0.0189

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: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Brier Loss	Nll	F1 Micro	F1 Macro	Ece	Aurc
No log	1.0	125	0.3896	0.893	0.1649	1.1887	0.893	0.8933	0.0484	0.0175
No log	2.0	250	0.3908	0.8948	0.1606	1.1433	0.8948	0.8950	0.0499	0.0179
No log	3.0	375	0.4188	0.892	0.1708	1.0860	0.892	0.8923	0.0607	0.0184
0.0953	4.0	500	0.4268	0.892	0.1707	1.0788	0.892	0.8924	0.0654	0.0184
0.0953	5.0	625	0.4414	0.8938	0.1719	1.0502	0.8938	0.8941	0.0664	0.0187
0.0953	6.0	750	0.4570	0.8932	0.1754	1.0253	0.8932	0.8936	0.0714	0.0187
0.0953	7.0	875	0.4681	0.891	0.1779	1.0018	0.891	0.8912	0.0752	0.0191
0.0128	8.0	1000	0.4720	0.8902	0.1792	0.9789	0.8902	0.8905	0.0771	0.0188
0.0128	9.0	1125	0.4757	0.8918	0.1794	0.9865	0.8918	0.8920	0.0760	0.0188
0.0128	10.0	1250	0.4776	0.8912	0.1798	0.9844	0.8912	0.8915	0.0768	0.0189

Framework versions

Transformers 4.33.3
Pytorch 2.2.0.dev20231002
Datasets 2.7.1
Tokenizers 0.13.3