Hugging Face's logo

alexgrigore
/
videomae-base-finetuned-good-gesturePhaseV5

Video Classification
Transformers
Safetensors
videomae
Generated from Trainer
Inference Endpoints
Model card Files Community
alexgrigore commited on
Commit
e63b5a6
•
1 Parent(s): 652b7f3

Model save

Browse files
Files changed (2) hide show
  1. README.md +85 -0
  2. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,85 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-nc-4.0
3
+ base_model: MCG-NJU/videomae-base
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - accuracy
8
+ model-index:
9
+ - name: videomae-base-finetuned-good-gesturePhaseV5
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # videomae-base-finetuned-good-gesturePhaseV5
17
+
18
+ This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Accuracy: 0.6871
21
+ - Loss: 0.9822
22
+ - Accuracy Hold: 0.0
23
+ - Accuracy Stroke: 0.0
24
+ - Accuracy Recovery: 0.0
25
+ - Accuracy Preparation: 0.9221
26
+ - Accuracy Unknown: 0.8571
27
+
28
+ ## Model description
29
+
30
+ More information needed
31
+
32
+ ## Intended uses & limitations
33
+
34
+ More information needed
35
+
36
+ ## Training and evaluation data
37
+
38
+ More information needed
39
+
40
+ ## Training procedure
41
+
42
+ ### Training hyperparameters
43
+
44
+ The following hyperparameters were used during training:
45
+ - learning_rate: 1e-05
46
+ - train_batch_size: 8
47
+ - eval_batch_size: 8
48
+ - seed: 42
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: linear
51
+ - lr_scheduler_warmup_ratio: 0.1
52
+ - training_steps: 1380
53
+
54
+ ### Training results
55
+
56
+ | Training Loss | Epoch | Step | Accuracy | Validation Loss | Accuracy Hold | Accuracy Stroke | Accuracy Recovery | Accuracy Preparation | Accuracy Unknown |
57
+ |:-------------:|:-------:|:----:|:--------:|:---------------:|:-------------:|:---------------:|:-----------------:|:--------------------:|:----------------:|
58
+ | 1.1475 | 0.0507 | 70 | 0.5597 | 1.2558 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
59
+ | 1.2103 | 1.0507 | 140 | 0.5597 | 1.2704 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
60
+ | 0.9964 | 2.0507 | 210 | 0.5597 | 1.2142 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
61
+ | 0.9975 | 3.0507 | 280 | 0.5970 | 1.0747 | 0.0 | 0.0 | 0.0 | 0.9733 | 0.2692 |
62
+ | 1.0538 | 4.0507 | 350 | 0.6642 | 0.9622 | 0.0 | 0.0 | 0.0 | 0.88 | 0.8846 |
63
+ | 1.0321 | 5.0507 | 420 | 0.6567 | 0.9451 | 0.0 | 0.0 | 0.0 | 0.8533 | 0.9231 |
64
+ | 0.7822 | 6.0507 | 490 | 0.7164 | 0.8797 | 0.0 | 0.0 | 0.0833 | 0.96 | 0.8846 |
65
+ | 0.8743 | 7.0507 | 560 | 0.6791 | 0.9399 | 0.0 | 0.0 | 0.0833 | 0.8533 | 1.0 |
66
+ | 0.7515 | 8.0507 | 630 | 0.6791 | 0.9290 | 0.0 | 0.0 | 0.0 | 0.8667 | 1.0 |
67
+ | 0.8525 | 9.0507 | 700 | 0.7090 | 0.8447 | 0.0 | 0.0 | 0.1667 | 0.9467 | 0.8462 |
68
+ | 0.7661 | 10.0507 | 770 | 0.7090 | 0.7857 | 0.0 | 0.0 | 0.1667 | 0.9067 | 0.9615 |
69
+ | 0.8363 | 11.0507 | 840 | 0.6866 | 0.8165 | 0.0 | 0.0 | 0.0833 | 0.92 | 0.8462 |
70
+ | 0.659 | 12.0507 | 910 | 0.7164 | 0.7951 | 0.0 | 0.0 | 0.1667 | 0.9067 | 1.0 |
71
+ | 0.6274 | 13.0507 | 980 | 0.7015 | 0.7754 | 0.0 | 0.0 | 0.0833 | 0.8933 | 1.0 |
72
+ | 0.7292 | 14.0507 | 1050 | 0.6791 | 0.8128 | 0.0 | 0.0 | 0.25 | 0.8267 | 1.0 |
73
+ | 0.7447 | 15.0507 | 1120 | 0.6866 | 0.7860 | 0.0 | 0.0 | 0.25 | 0.84 | 1.0 |
74
+ | 0.5512 | 16.0507 | 1190 | 0.7015 | 0.7839 | 0.0625 | 0.0 | 0.1667 | 0.8667 | 1.0 |
75
+ | 0.3404 | 17.0507 | 1260 | 0.7015 | 0.8055 | 0.0 | 0.0 | 0.3333 | 0.8533 | 1.0 |
76
+ | 0.4406 | 18.0507 | 1330 | 0.6866 | 0.7800 | 0.0 | 0.0 | 0.1667 | 0.8533 | 1.0 |
77
+ | 0.6358 | 19.0362 | 1380 | 0.7015 | 0.7816 | 0.0 | 0.0 | 0.1667 | 0.88 | 1.0 |
78
+
79
+
80
+ ### Framework versions
81
+
82
+ - Transformers 4.41.1
83
+ - Pytorch 2.3.0+cu121
84
+ - Datasets 2.19.1
85
+ - Tokenizers 0.19.1
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:bd2bbdfb117ca0d5002b7743a350dd7ec31b31e0e00b1dbd133a64a0845ab51d
3
  size 344946604
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9f4618f919ec3d642c730379e1b9f1a7ca1212ed23f72cce35bc4b8cad7a1e69
3
  size 344946604