Seed_Classifier – AI Model by mateoluksenberg | AlphaNeural AI | AlphaNeural AI

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mateoluksenberg/
Seed_Classifier

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image-classification

generated_from_trainer

microsoft/dit-base

autotrain_compatible

endpoints_compatible

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Seed_Classifier

This model is a fine-tuned version of microsoft/dit-base on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 2.6239
Accuracy: 0.0
Weighted f1: 0.0
Micro f1: 0.0
Macro f1: 0.0
Weighted recall: 0.0
Micro recall: 0.0
Macro recall: 0.0
Weighted precision: 0.0
Micro precision: 0.0
Macro precision: 0.0

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 18

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Weighted f1	Micro f1	Macro f1	Weighted recall	Micro recall	Macro recall	Weighted precision	Micro precision	Macro precision
0.3646	1.0	1	2.4555	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3646	2.0	2	2.4605	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3646	3.0	3	2.6009	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3646	4.0	4	2.7374	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3646	5.0	5	2.7640	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3646	6.0	6	2.7441	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3646	7.0	7	2.7820	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3442	8.0	8	2.8067	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3442	9.0	9	2.8143	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3442	10.0	10	2.7966	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3442	11.0	11	2.7836	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3442	12.0	12	2.7537	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3442	13.0	13	2.7233	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3442	14.0	14	2.6946	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3442	15.0	15	2.6638	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3003	16.0	16	2.6449	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3003	17.0	17	2.6312	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.3003	18.0	18	2.6239	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1