File size: 2,647 Bytes
a34aa21
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hftest-MHmae
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hftest-MHmae

This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.4422
- Accuracy: 0.156

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.97  | 19   | 6.0081          | 0.0026   |
| No log        | 1.99  | 39   | 5.9817          | 0.0034   |
| No log        | 2.96  | 58   | 5.9457          | 0.0084   |
| No log        | 3.99  | 78   | 5.9030          | 0.0118   |
| No log        | 4.96  | 97   | 5.8531          | 0.0204   |
| No log        | 5.98  | 117  | 5.8012          | 0.0338   |
| No log        | 6.95  | 136  | 5.7553          | 0.0458   |
| No log        | 7.97  | 156  | 5.7005          | 0.0666   |
| No log        | 9.0   | 176  | 5.6508          | 0.0842   |
| No log        | 9.97  | 195  | 5.6129          | 0.1006   |
| No log        | 10.99 | 215  | 5.5841          | 0.1108   |
| No log        | 11.96 | 234  | 5.5503          | 0.1208   |
| No log        | 12.98 | 254  | 5.5248          | 0.129    |
| No log        | 13.96 | 273  | 5.5014          | 0.1372   |
| No log        | 14.98 | 293  | 5.4761          | 0.1428   |
| No log        | 16.0  | 313  | 5.4660          | 0.1484   |
| No log        | 16.97 | 332  | 5.4574          | 0.1556   |
| No log        | 17.99 | 352  | 5.4520          | 0.1546   |
| No log        | 18.96 | 371  | 5.4458          | 0.1548   |
| No log        | 19.42 | 380  | 5.4422          | 0.156    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.1.0.dev20230627
- Datasets 2.13.1
- Tokenizers 0.13.3