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# videomae-base-finetuned-basketball-subset-20epochs

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: 2.8785
- Accuracy: 0.1972

## 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: 4060

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2525        | 0.05  | 200  | 0.7720          | 0.52     |
| 0.8649        | 1.05  | 400  | 0.7721          | 0.48     |
| 1.0703        | 2.05  | 600  | 1.3605          | 0.52     |
| 0.606         | 3.05  | 800  | 1.0668          | 0.6      |
| 2.0221        | 4.05  | 1000 | 1.1741          | 0.56     |
| 1.2916        | 5.05  | 1200 | 1.4747          | 0.52     |
| 1.4861        | 6.05  | 1400 | 1.1454          | 0.6      |
| 1.3012        | 7.05  | 1600 | 1.6105          | 0.56     |
| 1.3327        | 8.05  | 1800 | 1.2343          | 0.52     |
| 2.077         | 9.05  | 2000 | 1.3243          | 0.6      |
| 1.2349        | 10.05 | 2200 | 1.2044          | 0.6      |
| 1.005         | 11.05 | 2400 | 1.6417          | 0.52     |
| 1.1622        | 12.05 | 2600 | 1.3058          | 0.56     |
| 0.8031        | 13.05 | 2800 | 0.6776          | 0.48     |
| 0.8588        | 14.05 | 3000 | 1.1644          | 0.64     |
| 0.8451        | 15.05 | 3200 | 0.8491          | 0.64     |
| 1.1336        | 16.05 | 3400 | 1.0237          | 0.6      |
| 1.5719        | 17.05 | 3600 | 1.0391          | 0.64     |
| 0.4892        | 18.05 | 3800 | 0.9995          | 0.64     |
| 1.2092        | 19.05 | 4000 | 0.9802          | 0.56     |
| 0.9784        | 20.01 | 4060 | 0.9771          | 0.56     |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "videomae-base-finetuned-basketball-subset-20epochs", "results": []}]}
transformers pytorch tensorboard videomae video-classification generated_from_trainer license:cc-by-nc-4.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #videomae #video-classification #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 

videomae-base-finetuned-basketball-subset-20epochs
==================================================


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: 2.8785
* Accuracy: 0.1972


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: 4060


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### 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: 4060 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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: 4060 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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: 4060### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3