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# videomae-large-finetuned-kinetics-finetuned-engine-subset-R2-K400-20230418_3

This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1972
- Accuracy: 0.2647

## 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: 6
- eval_batch_size: 6
- 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: 2700

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5562        | 0.02  | 55   | 2.5746          | 0.0221   |
| 2.4543        | 1.02  | 110  | 2.5524          | 0.0956   |
| 2.1443        | 2.02  | 165  | 2.5214          | 0.1103   |
| 1.6604        | 3.02  | 220  | 2.6415          | 0.1397   |
| 1.5847        | 4.02  | 275  | 2.9843          | 0.0735   |
| 1.4657        | 5.02  | 330  | 2.7476          | 0.1471   |
| 1.0823        | 6.02  | 385  | 3.0872          | 0.1471   |
| 1.0672        | 7.02  | 440  | 2.9539          | 0.2206   |
| 0.7241        | 8.02  | 495  | 3.5364          | 0.1103   |
| 0.6532        | 9.02  | 550  | 3.1972          | 0.2647   |
| 0.6476        | 10.02 | 605  | 4.1289          | 0.0735   |
| 0.3725        | 11.02 | 660  | 4.4710          | 0.0588   |
| 0.7363        | 12.02 | 715  | 4.9241          | 0.0662   |
| 0.3136        | 13.02 | 770  | 4.8217          | 0.1176   |
| 0.3154        | 14.02 | 825  | 4.2717          | 0.1838   |
| 0.309         | 15.02 | 880  | 4.9466          | 0.0588   |
| 0.3094        | 16.02 | 935  | 5.5394          | 0.0147   |
| 0.3333        | 17.02 | 990  | 5.0940          | 0.0956   |
| 0.2299        | 18.02 | 1045 | 6.3148          | 0.0074   |
| 0.2257        | 19.02 | 1100 | 5.3869          | 0.0588   |
| 0.255         | 20.02 | 1155 | 6.4134          | 0.0147   |
| 0.2335        | 21.02 | 1210 | 6.1413          | 0.0441   |
| 0.3507        | 22.02 | 1265 | 6.2911          | 0.0074   |
| 0.1463        | 23.02 | 1320 | 6.5273          | 0.0074   |
| 0.193         | 24.02 | 1375 | 6.6533          | 0.0074   |
| 0.1167        | 25.02 | 1430 | 6.8094          | 0.0      |
| 0.1168        | 26.02 | 1485 | 6.7632          | 0.0      |
| 0.0511        | 27.02 | 1540 | 7.0046          | 0.0074   |
| 0.1336        | 28.02 | 1595 | 7.2877          | 0.0      |
| 0.1518        | 29.02 | 1650 | 7.3102          | 0.0      |
| 0.1972        | 30.02 | 1705 | 7.1632          | 0.0      |
| 0.0605        | 31.02 | 1760 | 7.2970          | 0.0      |
| 0.1633        | 32.02 | 1815 | 7.3427          | 0.0      |
| 0.1902        | 33.02 | 1870 | 7.4095          | 0.0      |
| 0.132         | 34.02 | 1925 | 7.3169          | 0.0      |
| 0.1226        | 35.02 | 1980 | 7.4196          | 0.0074   |
| 0.115         | 36.02 | 2035 | 7.3248          | 0.0074   |
| 0.1348        | 37.02 | 2090 | 7.1318          | 0.0      |
| 0.1684        | 38.02 | 2145 | 7.6482          | 0.0      |
| 0.0722        | 39.02 | 2200 | 7.5944          | 0.0074   |
| 0.1155        | 40.02 | 2255 | 7.5615          | 0.0      |
| 0.1425        | 41.02 | 2310 | 7.6454          | 0.0074   |
| 0.1552        | 42.02 | 2365 | 7.4774          | 0.0074   |
| 0.1078        | 43.02 | 2420 | 7.3991          | 0.0074   |
| 0.1169        | 44.02 | 2475 | 7.3240          | 0.0      |
| 0.1438        | 45.02 | 2530 | 7.4133          | 0.0      |
| 0.1227        | 46.02 | 2585 | 7.4592          | 0.0      |
| 0.0716        | 47.02 | 2640 | 7.5590          | 0.0      |
| 0.2077        | 48.02 | 2695 | 7.5708          | 0.0      |
| 0.0731        | 49.0  | 2700 | 7.5710          | 0.0      |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "videomae-large-finetuned-kinetics-finetuned-engine-subset-R2-K400-20230418_3", "results": []}]}
transformers pytorch videomae video-classification generated_from_trainer license:cc-by-nc-4.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #videomae #video-classification #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 

videomae-large-finetuned-kinetics-finetuned-engine-subset-R2-K400-20230418\_3
=============================================================================


This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 3.1972
* Accuracy: 0.2647


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: 6
* eval\_batch\_size: 6
* 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: 2700


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1+cu113
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 6
* eval\_batch\_size: 6
* 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: 2700 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1+cu113
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #videomae #video-classification #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 6
* eval\_batch\_size: 6
* 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: 2700 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1+cu113
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #videomae #video-classification #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 6
* eval\_batch\_size: 6
* 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: 2700### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1+cu113
* Datasets 2.10.1
* Tokenizers 0.13.2