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# assist_vc

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: 0.9840
- Accuracy: 0.6842

## 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: 1
- eval_batch_size: 1
- 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: 160

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7497        | 0.1   | 16   | 1.6563          | 0.1316   |
| 1.7873        | 1.1   | 32   | 1.3495          | 0.6842   |
| 0.7577        | 2.1   | 48   | 1.5793          | 0.5526   |
| 1.6926        | 3.1   | 64   | 1.7424          | 0.5526   |
| 1.9555        | 4.1   | 80   | 1.3199          | 0.5263   |
| 1.3076        | 5.1   | 96   | 1.5087          | 0.6842   |
| 2.4857        | 6.1   | 112  | 1.3040          | 0.6842   |
| 0.8124        | 7.1   | 128  | 1.0371          | 0.6842   |
| 2.0312        | 8.1   | 144  | 1.0630          | 0.6842   |
| 1.1519        | 9.1   | 160  | 0.9840          | 0.6842   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "assist_vc", "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 

assist\_vc
==========


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: 0.9840
* Accuracy: 0.6842


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: 1
* eval\_batch\_size: 1
* 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: 160


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* 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: 160 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* 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: 1
* eval\_batch\_size: 1
* 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: 160 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* 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: 1
* eval\_batch\_size: 1
* 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: 160### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* Tokenizers 0.13.2