working – AI Model by Shawon16 | AlphaNeural AI

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MCG-NJU/videomae-base

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working

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 4.6095
Accuracy: 0.0266
Top 1 Accuracy: 0.0266
Top 5 Accuracy: 0.0858
Top 10 Accuracy: 0.1420
Macro Precision: 0.0024
Macro Recall: 0.0173
Macro F1: 0.0039
Pearson Corr: 0.3016
Spearman Corr: 0.2739

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 900
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Top 1 Accuracy	Top 5 Accuracy	Top 10 Accuracy	Macro Precision	Macro Recall	Macro F1	Pearson Corr	Spearman Corr
4.523	5.0542	500	4.6095	0.0266	0.0266	0.0858	0.1420	0.0024	0.0173	0.0039	0.3016	0.2739

Framework versions

Transformers 4.44.0
Pytorch 1.11.0+cu102
Datasets 2.21.0
Tokenizers 0.19.1