Hugging Face's logo

Kartikeya
/
videomae-base-finetuned-yt_short_classification-2

Video Classification
Transformers
Safetensors
videomae
Generated from Trainer
Model card Files Community
Kartikeya commited on
Commit
6a662ec
·
verified ·
1 Parent(s): 0136ac5

Model save

Browse files
Files changed (2) hide show
  1. README.md +88 -0
  2. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,88 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: cc-by-nc-4.0
4
+ base_model: MCG-NJU/videomae-base
5
+ tags:
6
+ - generated_from_trainer
7
+ metrics:
8
+ - accuracy
9
+ model-index:
10
+ - name: videomae-base-finetuned-yt_short_classification-2
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-base-finetuned-yt_short_classification-2
18
+
19
+ This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 0.4733
22
+ - Accuracy: 0.7818
23
+ - 0 Precision: 0.7333
24
+ - 0 Recall: 0.8515
25
+ - 0 F1-score: 0.7880
26
+ - 0 Support: 6322.0
27
+ - 1 Precision: 0.8419
28
+ - 1 Recall: 0.7186
29
+ - 1 F1-score: 0.7753
30
+ - 1 Support: 6957.0
31
+ - Accuracy F1-score: 0.7818
32
+ - Macro avg Precision: 0.7876
33
+ - Macro avg Recall: 0.7850
34
+ - Macro avg F1-score: 0.7817
35
+ - Macro avg Support: 13279.0
36
+ - Weighted avg Precision: 0.7902
37
+ - Weighted avg Recall: 0.7818
38
+ - Weighted avg F1-score: 0.7814
39
+ - Weighted avg Support: 13279.0
40
+
41
+ ## Model description
42
+
43
+ More information needed
44
+
45
+ ## Intended uses & limitations
46
+
47
+ More information needed
48
+
49
+ ## Training and evaluation data
50
+
51
+ More information needed
52
+
53
+ ## Training procedure
54
+
55
+ ### Training hyperparameters
56
+
57
+ The following hyperparameters were used during training:
58
+ - learning_rate: 5e-05
59
+ - train_batch_size: 16
60
+ - eval_batch_size: 16
61
+ - seed: 42
62
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
63
+ - lr_scheduler_type: linear
64
+ - lr_scheduler_warmup_ratio: 0.1
65
+ - training_steps: 4120
66
+
67
+ ### Training results
68
+
69
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | 0 Precision | 0 Recall | 0 F1-score | 0 Support | 1 Precision | 1 Recall | 1 F1-score | 1 Support | Accuracy F1-score | Macro avg Precision | Macro avg Recall | Macro avg F1-score | Macro avg Support | Weighted avg Precision | Weighted avg Recall | Weighted avg F1-score | Weighted avg Support |
70
+ |:-------------:|:------:|:----:|:---------------:|:--------:|:-----------:|:--------:|:----------:|:---------:|:-----------:|:--------:|:----------:|:---------:|:-----------------:|:-------------------:|:----------------:|:------------------:|:-----------------:|:----------------------:|:-------------------:|:---------------------:|:--------------------:|
71
+ | 0.6122 | 0.1002 | 413 | 0.7143 | 0.6551 | 0.5925 | 0.8828 | 0.7091 | 6322.0 | 0.8080 | 0.4482 | 0.5766 | 6957.0 | 0.6551 | 0.7002 | 0.6655 | 0.6428 | 13279.0 | 0.7054 | 0.6551 | 0.6396 | 13279.0 |
72
+ | 0.6904 | 1.1002 | 826 | 0.5800 | 0.6909 | 0.8170 | 0.4519 | 0.5819 | 6322.0 | 0.6458 | 0.9080 | 0.7548 | 6957.0 | 0.6909 | 0.7314 | 0.6800 | 0.6683 | 13279.0 | 0.7273 | 0.6909 | 0.6725 | 13279.0 |
73
+ | 0.5489 | 2.1002 | 1239 | 0.5122 | 0.7555 | 0.7450 | 0.7395 | 0.7422 | 6322.0 | 0.7648 | 0.7700 | 0.7674 | 6957.0 | 0.7555 | 0.7549 | 0.7547 | 0.7548 | 13279.0 | 0.7554 | 0.7555 | 0.7554 | 13279.0 |
74
+ | 0.4979 | 3.1002 | 1652 | 0.5434 | 0.7443 | 0.6785 | 0.8798 | 0.7662 | 6322.0 | 0.8505 | 0.6212 | 0.7180 | 6957.0 | 0.7443 | 0.7645 | 0.7505 | 0.7421 | 13279.0 | 0.7686 | 0.7443 | 0.7409 | 13279.0 |
75
+ | 0.5141 | 4.1002 | 2065 | 0.4793 | 0.7723 | 0.7482 | 0.7866 | 0.7669 | 6322.0 | 0.7966 | 0.7594 | 0.7775 | 6957.0 | 0.7723 | 0.7724 | 0.7730 | 0.7722 | 13279.0 | 0.7735 | 0.7723 | 0.7725 | 13279.0 |
76
+ | 0.4472 | 5.1002 | 2478 | 0.4673 | 0.7798 | 0.7398 | 0.8290 | 0.7819 | 6322.0 | 0.8255 | 0.7351 | 0.7777 | 6957.0 | 0.7798 | 0.7827 | 0.7820 | 0.7798 | 13279.0 | 0.7847 | 0.7798 | 0.7797 | 13279.0 |
77
+ | 0.4108 | 6.1002 | 2891 | 0.4491 | 0.7952 | 0.7715 | 0.8096 | 0.7901 | 6322.0 | 0.8188 | 0.7821 | 0.8000 | 6957.0 | 0.7952 | 0.7951 | 0.7958 | 0.7950 | 13279.0 | 0.7963 | 0.7952 | 0.7953 | 13279.0 |
78
+ | 0.3756 | 7.1002 | 3304 | 0.4955 | 0.7773 | 0.7472 | 0.8045 | 0.7748 | 6322.0 | 0.8090 | 0.7526 | 0.7798 | 6957.0 | 0.7773 | 0.7781 | 0.7786 | 0.7773 | 13279.0 | 0.7796 | 0.7773 | 0.7774 | 13279.0 |
79
+ | 0.3147 | 8.1002 | 3717 | 0.5889 | 0.7318 | 0.6523 | 0.9348 | 0.7684 | 6322.0 | 0.9023 | 0.5472 | 0.6813 | 6957.0 | 0.7318 | 0.7773 | 0.7410 | 0.7249 | 13279.0 | 0.7833 | 0.7318 | 0.7228 | 13279.0 |
80
+ | 0.4019 | 9.0978 | 4120 | 0.4733 | 0.7818 | 0.7333 | 0.8515 | 0.7880 | 6322.0 | 0.8419 | 0.7186 | 0.7753 | 6957.0 | 0.7818 | 0.7876 | 0.7850 | 0.7817 | 13279.0 | 0.7902 | 0.7818 | 0.7814 | 13279.0 |
81
+
82
+
83
+ ### Framework versions
84
+
85
+ - Transformers 4.46.3
86
+ - Pytorch 2.0.0+cu117
87
+ - Datasets 3.1.0
88
+ - Tokenizers 0.20.3
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6ce07a438cfdc4e4398517a7fcc4823be6f6b8a0ab3125cc5ac757f622aac922
3
  size 344937368
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a1d14fd489c32d7bbc4dda237f570d8652c86d682ff30a9c08d1e4aab5f60762
3
  size 344937368