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huahua1
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MCG-NJUvideomae-base-finetuned-kinetics-face

Video Classification
Transformers
Safetensors
videomae
Generated from Trainer
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  1. README.md +68 -20
  2. model.safetensors +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0041
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- - Accuracy: 1.0
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  ## Model description
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@@ -37,35 +37,83 @@ More information needed
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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: 5
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- - eval_batch_size: 5
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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: 1200
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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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- | 0.3113 | 16.0033 | 100 | 0.2366 | 0.9167 |
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- | 0.0245 | 33.0017 | 200 | 1.0873 | 0.8333 |
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- | 0.0221 | 49.005 | 300 | 0.4646 | 0.9167 |
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- | 0.1456 | 66.0033 | 400 | 0.2763 | 0.9167 |
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- | 0.1463 | 83.0017 | 500 | 0.2295 | 0.8889 |
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- | 0.0005 | 99.005 | 600 | 0.1902 | 0.9444 |
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- | 0.0008 | 116.0033 | 700 | 0.0679 | 0.9722 |
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- | 0.002 | 133.0017 | 800 | 0.2619 | 0.9444 |
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- | 0.0002 | 149.005 | 900 | 0.8475 | 0.8889 |
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- | 0.0002 | 166.0033 | 1000 | 0.4333 | 0.8889 |
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- | 0.0003 | 183.0017 | 1100 | 0.0015 | 1.0 |
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- | 0.0002 | 199.005 | 1200 | 0.0041 | 1.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.45.0
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  - Pytorch 2.4.1+cu118
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- - Datasets 3.0.0
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- - Tokenizers 0.20.0
 
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7299
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+ - Accuracy: 0.9167
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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: 6000
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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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+ | 1.5489 | 3.0017 | 100 | 1.5109 | 0.6111 |
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+ | 0.6115 | 6.0033 | 200 | 0.5476 | 1.0 |
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+ | 0.042 | 9.005 | 300 | 0.0697 | 1.0 |
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+ | 0.0243 | 13.0017 | 400 | 0.1967 | 0.9167 |
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+ | 1.1668 | 16.0033 | 500 | 0.9849 | 0.8333 |
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+ | 0.1354 | 19.005 | 600 | 0.7017 | 0.8333 |
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+ | 0.8714 | 23.0017 | 700 | 0.0027 | 1.0 |
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+ | 0.0009 | 26.0033 | 800 | 0.2290 | 0.9444 |
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+ | 0.0003 | 29.005 | 900 | 0.1073 | 0.9722 |
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+ | 1.0037 | 33.0017 | 1000 | 1.3122 | 0.75 |
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+ | 0.4275 | 36.0033 | 1100 | 0.0041 | 1.0 |
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+ | 0.0005 | 39.005 | 1200 | 0.3496 | 0.9444 |
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+ | 0.0005 | 43.0017 | 1300 | 0.1043 | 0.9722 |
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+ | 0.0239 | 46.0033 | 1400 | 1.4939 | 0.8333 |
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+ | 0.0174 | 49.005 | 1500 | 0.0428 | 0.9722 |
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+ | 0.001 | 53.0017 | 1600 | 0.6678 | 0.8889 |
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+ | 0.0865 | 56.0033 | 1700 | 0.3907 | 0.9444 |
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+ | 0.9919 | 59.005 | 1800 | 0.0019 | 1.0 |
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+ | 0.0007 | 63.0017 | 1900 | 0.7224 | 0.8889 |
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+ | 0.0002 | 66.0033 | 2000 | 0.0023 | 1.0 |
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+ | 0.0002 | 69.005 | 2100 | 0.2816 | 0.9444 |
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+ | 0.7678 | 73.0017 | 2200 | 1.0904 | 0.8056 |
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+ | 0.0013 | 76.0033 | 2300 | 1.0187 | 0.8611 |
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+ | 0.0004 | 79.005 | 2400 | 0.2458 | 0.9722 |
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+ | 0.0094 | 83.0017 | 2500 | 0.9661 | 0.8333 |
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+ | 0.0003 | 86.0033 | 2600 | 0.2274 | 0.9722 |
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+ | 0.0011 | 89.005 | 2700 | 0.2844 | 0.9444 |
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+ | 0.0001 | 93.0017 | 2800 | 0.8405 | 0.8611 |
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+ | 0.0001 | 96.0033 | 2900 | 0.5875 | 0.9167 |
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+ | 0.0001 | 99.005 | 3000 | 1.8345 | 0.7778 |
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+ | 0.0001 | 103.0017 | 3100 | 0.5098 | 0.9167 |
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+ | 0.0003 | 106.0033 | 3200 | 0.0062 | 1.0 |
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+ | 0.3248 | 109.005 | 3300 | 0.4113 | 0.9444 |
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+ | 0.0001 | 113.0017 | 3400 | 0.1064 | 0.9722 |
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+ | 0.0001 | 116.0033 | 3500 | 0.0006 | 1.0 |
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+ | 0.0003 | 119.005 | 3600 | 0.2552 | 0.9722 |
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+ | 0.001 | 123.0017 | 3700 | 0.0202 | 1.0 |
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+ | 0.0002 | 126.0033 | 3800 | 0.3475 | 0.9444 |
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+ | 0.0001 | 129.005 | 3900 | 0.5493 | 0.9444 |
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+ | 0.0001 | 133.0017 | 4000 | 0.5506 | 0.9444 |
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+ | 0.0001 | 136.0033 | 4100 | 0.5711 | 0.9167 |
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+ | 0.0001 | 139.005 | 4200 | 0.5181 | 0.9444 |
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+ | 0.0021 | 143.0017 | 4300 | 0.7568 | 0.9167 |
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+ | 0.9007 | 146.0033 | 4400 | 0.0072 | 1.0 |
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+ | 0.0001 | 149.005 | 4500 | 0.2858 | 0.9444 |
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+ | 0.0001 | 153.0017 | 4600 | 1.0247 | 0.8889 |
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+ | 0.6131 | 156.0033 | 4700 | 0.0814 | 0.9722 |
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+ | 0.0004 | 159.005 | 4800 | 1.8986 | 0.8056 |
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+ | 0.0001 | 163.0017 | 4900 | 1.5607 | 0.8056 |
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+ | 0.0001 | 166.0033 | 5000 | 1.5370 | 0.8056 |
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+ | 0.0001 | 169.005 | 5100 | 1.4807 | 0.8056 |
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+ | 0.0001 | 173.0017 | 5200 | 1.2996 | 0.8333 |
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+ | 0.0 | 176.0033 | 5300 | 1.2259 | 0.8056 |
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+ | 0.0001 | 179.005 | 5400 | 1.1819 | 0.8056 |
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+ | 0.0 | 183.0017 | 5500 | 1.1047 | 0.8056 |
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+ | 0.0001 | 186.0033 | 5600 | 1.0461 | 0.8333 |
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+ | 0.0 | 189.005 | 5700 | 1.2544 | 0.8056 |
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+ | 0.8628 | 193.0017 | 5800 | 1.1260 | 0.8056 |
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+ | 0.0 | 196.0033 | 5900 | 0.7299 | 0.9167 |
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+ | 0.0 | 199.005 | 6000 | 0.7299 | 0.9167 |
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  ### Framework versions
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+ - Transformers 4.45.2
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  - Pytorch 2.4.1+cu118
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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