dit-tiny_tobacco3482_kd_CEKD_t2.5_a0.7

jordyvl/dit-tiny_tobacco3482_kd_CEKD_t2.5_a0.7

dit-tiny_tobacco3482_kd_CEKD_t2.5_a0.7 is a image classification model from jordyvl. Use it when you need a label for an image. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Classification
Library: transformers
Model type: beit
Access: Public
Created: Jul 9, 2023
Updated: Jul 9, 2023
SHA: 584245b3

Model card

From the Hugging Face model README

dit-tiny_tobacco3482_kd_CEKD_t2.5_a0.7

This model is a fine-tuned version of microsoft/dit-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.2510
Accuracy: 0.18
Brier Loss: 0.8767
Nll: 6.8039
F1 Micro: 0.18
F1 Macro: 0.0306
Ece: 0.2513
Aurc: 0.8508

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Brier Loss	Nll	F1 Micro	F1 Macro	Ece	Aurc
No log	0.96	3	3.4586	0.145	0.8999	10.1587	0.145	0.0253	0.2221	0.8467
No log	1.96	6	3.4232	0.145	0.8946	10.5824	0.145	0.0253	0.2242	0.8475
No log	2.96	9	3.3704	0.16	0.8867	8.6135	0.16	0.0503	0.2171	0.8440
No log	3.96	12	3.3273	0.155	0.8807	6.5471	0.155	0.0274	0.2248	0.8831
No log	4.96	15	3.3006	0.155	0.8779	6.8045	0.155	0.0271	0.2331	0.8918
No log	5.96	18	3.2856	0.16	0.8773	8.2046	0.16	0.0329	0.2361	0.8956
No log	6.96	21	3.2758	0.18	0.8774	8.0738	0.18	0.0308	0.2561	0.8544
No log	7.96	24	3.2688	0.18	0.8778	7.1046	0.18	0.0308	0.2647	0.8524
No log	8.96	27	3.2630	0.18	0.8778	6.9910	0.18	0.0306	0.2591	0.8530
No log	9.96	30	3.2597	0.18	0.8778	6.9680	0.18	0.0306	0.2736	0.8538
No log	10.96	33	3.2573	0.18	0.8776	6.9547	0.18	0.0306	0.2698	0.8536
No log	11.96	36	3.2557	0.18	0.8775	6.9491	0.18	0.0306	0.2653	0.8533
No log	12.96	39	3.2546	0.18	0.8773	6.8987	0.18	0.0306	0.2606	0.8526
No log	13.96	42	3.2536	0.18	0.8771	6.8204	0.18	0.0306	0.2601	0.8523
No log	14.96	45	3.2528	0.18	0.8771	6.8141	0.18	0.0306	0.2521	0.8519
No log	15.96	48	3.2522	0.18	0.8769	6.8074	0.18	0.0306	0.2606	0.8517
No log	16.96	51	3.2519	0.18	0.8769	6.8077	0.18	0.0306	0.2607	0.8515
No log	17.96	54	3.2520	0.18	0.8769	6.8050	0.18	0.0306	0.2561	0.8510
No log	18.96	57	3.2520	0.18	0.8769	6.8057	0.18	0.0306	0.2519	0.8509
No log	19.96	60	3.2515	0.18	0.8768	6.8046	0.18	0.0306	0.2556	0.8507
No log	20.96	63	3.2514	0.18	0.8768	6.8048	0.18	0.0306	0.2515	0.8506
No log	21.96	66	3.2512	0.18	0.8767	6.8048	0.18	0.0306	0.2556	0.8508
No log	22.96	69	3.2510	0.18	0.8767	6.8045	0.18	0.0306	0.2513	0.8509
No log	23.96	72	3.2510	0.18	0.8767	6.8043	0.18	0.0306	0.2513	0.8508
No log	24.96	75	3.2510	0.18	0.8767	6.8039	0.18	0.0306	0.2513	0.8508

Framework versions

Transformers 4.26.1
Pytorch 1.13.1.post200
Datasets 2.9.0
Tokenizers 0.13.2

Task: Image Classification
Library: transformers
Type: beit
Created: Jul 9, 2023
Updated: Jul 9, 2023