README.md
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1 ---
2 library_name: transformers
3 license: cc-by-nc-4.0
4 base_model: MCG-NJU/videomae-small-finetuned-kinetics
5 tags:
6 - generated_from_trainer
7 metrics:
8 - accuracy
9 model-index:
10 - name: videomae-small-finetuned-kinetics-finetuned-xd-violence
11 results: []
12 ---
13
14 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15 should probably proofread and complete it, then remove this comment. -->
16
17 # videomae-small-finetuned-kinetics-finetuned-xd-violence
18
19 This model is a fine-tuned version of [MCG-NJU/videomae-small-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-small-finetuned-kinetics) on an unknown dataset.
20 It achieves the following results on the evaluation set:
21 - Loss: 0.3828
22 - Accuracy: 0.8254
23
24
25 Video preprocessing config:
26 Resize to: (224, 224)
27 Frames to sample: 16
28 Clip duration: 2.1333333333333333s
29
30 ## Model description
31
32 More information needed
33
34 ## Intended uses & limitations
35
36 More information needed
37
38 ## Training and evaluation data
39
40 More information needed
41
42 ## Training procedure
43
44 ### Training hyperparameters
45
46 The following hyperparameters were used during training:
47 - learning_rate: 5e-05
48 - train_batch_size: 2
49 - eval_batch_size: 2
50 - seed: 42
51 - gradient_accumulation_steps: 4
52 - total_train_batch_size: 8
53 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
54 - lr_scheduler_type: linear
55 - lr_scheduler_warmup_ratio: 0.1
56 - num_epochs: 3
57
58 ### Training results
59
60 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
61 |:-------------:|:-----:|:----:|:---------------:|:--------:|
62 | 0.3574 | 1.0 | 394 | 0.5181 | 0.7738 |
63 | 0.4428 | 2.0 | 788 | 0.4357 | 0.8119 |
64 | 0.075 | 3.0 | 1182 | 0.4100 | 0.8183 |
65
66
67 ### Testing results
68
69 ```
70 {'eval_loss': 0.3827999532222748,
71 'eval_accuracy': 0.8253768844221105,
72 'eval_runtime': 184.3164,
73 'eval_samples_per_second': 4.319,
74 'eval_steps_per_second': 2.159,
75 'epoch': 3.0}
76 ```
77
78 | Class | Precision | Recall | F1-Score | Support |
79 | :--- | :--- | :--- | :--- | :--- |
80 | **Normal (0)** | 0.74 | 0.83 | 0.78 | 299 |
81 | **Violent (1)** | 0.89 | 0.82 | 0.85 | 497 |
82 | | | | | |
83 | **Accuracy** | | | 0.83 | 796 |
84 | **Macro Avg** | 0.81 | 0.83 | 0.82 | 796 |
85 | **Weighted Avg** | 0.83 | 0.83 | 0.83 | 796 |
86
87 ### Framework versions
88
89 - Transformers 4.57.1
90 - Pytorch 2.8.0+cu126
91 - Datasets 4.0.0
92 - Tokenizers 0.22.1
93