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prathameshdalal
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videomae-base-finetuned-ucf101-subset

Video Classification
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videomae
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End of training

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  1. README.md +20 -8
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1896
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- - Accuracy: 0.9429
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 2
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- - eval_batch_size: 2
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.5443 | 0.25 | 150 | 1.2805 | 0.4714 |
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- | 0.7116 | 1.25 | 300 | 0.6705 | 0.7 |
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- | 0.122 | 2.25 | 450 | 0.3157 | 0.8857 |
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- | 0.0669 | 3.25 | 600 | 0.1896 | 0.9429 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1362
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+ - Accuracy: 0.9714
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.2638 | 0.06 | 38 | 2.2761 | 0.1143 |
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+ | 1.6112 | 1.06 | 76 | 1.0811 | 0.7143 |
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+ | 0.5768 | 2.06 | 114 | 0.4538 | 0.8857 |
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+ | 0.298 | 3.06 | 152 | 0.4841 | 0.8 |
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+ | 0.0856 | 4.06 | 190 | 0.6021 | 0.8 |
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+ | 0.2283 | 5.06 | 228 | 0.2103 | 0.9286 |
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+ | 0.0559 | 6.06 | 266 | 0.1142 | 0.9714 |
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+ | 0.2279 | 7.06 | 304 | 0.1132 | 0.9714 |
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+ | 0.0145 | 8.06 | 342 | 0.0762 | 0.9714 |
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+ | 0.0057 | 9.06 | 380 | 0.0226 | 1.0 |
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+ | 0.0076 | 10.06 | 418 | 0.1619 | 0.9714 |
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+ | 0.0046 | 11.06 | 456 | 0.1617 | 0.9714 |
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+ | 0.0034 | 12.06 | 494 | 0.1676 | 0.9571 |
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+ | 0.0034 | 13.06 | 532 | 0.1398 | 0.9714 |
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+ | 0.0034 | 14.06 | 570 | 0.1345 | 0.9714 |
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+ | 0.0035 | 15.05 | 600 | 0.1362 | 0.9714 |
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  ### Framework versions
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