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videomae-base-finetuned-kinetics-finetuned-ucf101-subset-finetuned-N

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
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  1. README.md +5 -11
  2. model.safetensors +1 -1
  3. runs/Nov21_13-28-29_7ebbed072e6e/events.out.tfevents.1700573800.7ebbed072e6e.762.4 +3 -0
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 [sayakpaul/videomae-base-finetuned-kinetics-finetuned-ucf101-subset](https://huggingface.co/sayakpaul/videomae-base-finetuned-kinetics-finetuned-ucf101-subset) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3578
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- - Accuracy: 0.8387
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  ## Model description
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@@ -44,24 +44,18 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - training_steps: 77
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.9326 | 0.16 | 12 | 0.6945 | 0.6316 |
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- | 0.5856 | 1.16 | 24 | 0.5931 | 0.5789 |
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- | 0.3968 | 2.16 | 36 | 0.4350 | 0.7368 |
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- | 0.362 | 3.16 | 48 | 0.6303 | 0.7105 |
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- | 0.1438 | 4.16 | 60 | 0.7715 | 0.6842 |
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- | 0.0632 | 5.16 | 72 | 0.8964 | 0.6579 |
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- | 0.0632 | 6.06 | 77 | 0.9021 | 0.6842 |
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu118
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- - Datasets 2.15.0
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  - Tokenizers 0.15.0
 
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  This model is a fine-tuned version of [sayakpaul/videomae-base-finetuned-kinetics-finetuned-ucf101-subset](https://huggingface.co/sayakpaul/videomae-base-finetuned-kinetics-finetuned-ucf101-subset) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4188
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+ - Accuracy: 0.8605
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 308
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4843 | 0.5 | 155 | 0.4956 | 0.8045 |
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+ | 0.532 | 1.5 | 308 | 0.4924 | 0.8045 |
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu118
 
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  - Tokenizers 0.15.0
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runs/Nov21_13-28-29_7ebbed072e6e/events.out.tfevents.1700573800.7ebbed072e6e.762.4 ADDED
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