resnet-50-finetuned-FER2013-0.003 – AI Model by Celal11 | AlphaNeural AI

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Celal11/
resnet-50-finetuned-FER2013-0.003

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image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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resnet-50-finetuned-FER2013-0.003

This model is a fine-tuned version of microsoft/resnet-50 on the image_folder dataset. It achieves the following results on the evaluation set:

Loss: 0.9036
Accuracy: 0.6971

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: 0.003
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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4393	1.0	224	1.2746	0.5173
1.2564	2.0	448	1.1456	0.5542
1.218	3.0	672	1.1102	0.5816
1.1919	4.0	896	1.0255	0.6151
1.1222	5.0	1120	1.0257	0.6167
1.0925	6.0	1344	0.9676	0.6317
1.0241	7.0	1568	0.9406	0.6510
1.0015	8.0	1792	0.9465	0.6532
0.987	9.0	2016	0.9002	0.6748
0.9768	10.0	2240	0.9086	0.6737
0.9408	11.0	2464	0.8975	0.6793
0.8907	12.0	2688	0.8966	0.6769
0.8051	13.0	2912	0.9142	0.6826
0.8169	14.0	3136	0.9082	0.6870
0.7729	15.0	3360	0.9036	0.6971

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1