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asmaa1
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videomae-base-groub2-finetuned-SLT-subset

Video Classification
Transformers
PyTorch
videomae
Generated from Trainer
Inference Endpoints
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  1. README.md +24 -11
  2. pytorch_model.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: 2.8934
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- - Accuracy: 0.1429
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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: 1
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- - eval_batch_size: 1
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - training_steps: 63
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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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- | 3.4317 | 0.33 | 21 | 2.9835 | 0.0952 |
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- | 3.2385 | 1.33 | 42 | 2.9287 | 0.1429 |
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- | 3.0757 | 2.33 | 63 | 2.8934 | 0.1429 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.33.0
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- - Pytorch 2.0.0+cpu
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- - Datasets 2.1.0
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  - Tokenizers 0.13.3
 
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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: 0.2405
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+ - Accuracy: 1.0
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 960
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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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+ | 3.928 | 0.06 | 61 | 3.6624 | 0.0244 |
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+ | 3.8332 | 1.06 | 122 | 3.5354 | 0.0732 |
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+ | 3.5587 | 2.06 | 183 | 3.2996 | 0.0976 |
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+ | 3.4907 | 3.06 | 244 | 3.1796 | 0.0976 |
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+ | 3.4674 | 4.06 | 305 | 3.1159 | 0.0976 |
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+ | 3.5079 | 5.06 | 366 | 3.0202 | 0.1220 |
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+ | 2.9034 | 6.06 | 427 | 2.8292 | 0.1707 |
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+ | 2.9286 | 7.06 | 488 | 2.4582 | 0.6098 |
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+ | 2.4388 | 8.06 | 549 | 1.8469 | 0.7317 |
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+ | 1.7172 | 9.06 | 610 | 1.2915 | 0.8537 |
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+ | 1.2504 | 10.06 | 671 | 0.8991 | 0.9512 |
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+ | 0.974 | 11.06 | 732 | 0.5943 | 0.9268 |
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+ | 0.4528 | 12.06 | 793 | 0.4040 | 0.9512 |
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+ | 0.3593 | 13.06 | 854 | 0.3052 | 1.0 |
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+ | 0.2068 | 14.06 | 915 | 0.2569 | 1.0 |
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+ | 0.185 | 15.05 | 960 | 0.2405 | 1.0 |
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  ### Framework versions
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+ - Transformers 4.33.3
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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  - Tokenizers 0.13.3
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