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videomae-base-short-finetuned-rwf2000 – AI Model by lmazzon70 | AlphaNeural AI | AlphaNeural AI
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lmazzon70
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videomae-base-short-finetuned-rwf2000
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transformers
pytorch
tensorboard
videomae
video-classification
generated_from_trainer
cc-by-nc-4.0
endpoints_compatible
us
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videomae-base-short-finetuned-rwf2000
This model is a fine-tuned version of
MCG-NJU/videomae-base-short
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.2655
Accuracy: 0.3714
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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 3200
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3657
0.25
800
0.6160
0.7837
0.8426
1.25
1600
1.3039
0.665
0.0154
2.25
2400
1.3218
0.6937
0.1594
3.25
3200
0.9938
0.7575
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2
