File size: 1,750 Bytes
2eec64d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-ssv2-finetuned-rwf2000-epochs6
  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. -->

# videomae-base-ssv2-finetuned-rwf2000-epochs6

This model is a fine-tuned version of [MCG-NJU/videomae-base-ssv2](https://huggingface.co/MCG-NJU/videomae-base-ssv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7920
- Accuracy: 0.4357

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 4800

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.841         | 0.17  | 800  | 0.7114          | 0.755    |
| 0.8781        | 1.17  | 1600 | 1.6078          | 0.5925   |
| 0.1951        | 2.17  | 2400 | 1.9190          | 0.5962   |
| 0.2094        | 3.17  | 3200 | 0.9991          | 0.7588   |
| 0.3594        | 4.17  | 4000 | 1.0306          | 0.7937   |
| 0.0019        | 5.17  | 4800 | 1.0982          | 0.7775   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2