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# videomae-base-finetuned-basketball-subset-v3-25epoch

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: 0.8922
- Accuracy: 0.9

## 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: 5100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2489        | 0.04  | 202  | 0.7252          | 0.7      |
| 0.5366        | 1.04  | 404  | 1.2745          | 0.6      |
| 0.9659        | 2.04  | 606  | 0.7013          | 0.85     |
| 0.0226        | 3.04  | 808  | 1.3065          | 0.7      |
| 0.5437        | 4.04  | 1010 | 2.0397          | 0.7      |
| 0.0002        | 5.04  | 1212 | 1.8936          | 0.75     |
| 0.0003        | 6.04  | 1414 | 1.4473          | 0.8      |
| 0.0193        | 7.04  | 1616 | 1.1602          | 0.75     |
| 0.0001        | 8.04  | 1818 | 0.8922          | 0.9      |
| 0.0001        | 9.04  | 2020 | 1.0781          | 0.85     |
| 0.0           | 10.04 | 2222 | 1.1948          | 0.85     |
| 0.0           | 11.04 | 2424 | 1.2431          | 0.85     |
| 0.0           | 12.04 | 2626 | 1.2794          | 0.85     |
| 0.0           | 13.04 | 2828 | 1.3082          | 0.85     |
| 0.0           | 14.04 | 3030 | 1.3332          | 0.85     |
| 0.0           | 15.04 | 3232 | 1.3539          | 0.85     |
| 0.0           | 16.04 | 3434 | 1.3793          | 0.85     |
| 0.0           | 17.04 | 3636 | 1.4510          | 0.8      |
| 0.0           | 18.04 | 3838 | 1.5646          | 0.8      |
| 0.0           | 19.04 | 4040 | 1.6535          | 0.8      |
| 0.0           | 20.04 | 4242 | 1.7017          | 0.8      |
| 0.0           | 21.04 | 4444 | 1.7366          | 0.8      |
| 0.0           | 22.04 | 4646 | 1.7639          | 0.8      |
| 0.0           | 23.04 | 4848 | 1.7792          | 0.8      |
| 0.0           | 24.04 | 5050 | 1.7855          | 0.8      |
| 0.0           | 25.01 | 5100 | 1.7857          | 0.8      |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "videomae-base-finetuned-basketball-subset-v3-25epoch", "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-v3-25epoch
====================================================


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: 0.8922
* Accuracy: 0.9


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: 5100


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1+cu116
* Datasets 2.4.0
* Tokenizers 0.12.1



### 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: 5100 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1+cu116
* Datasets 2.4.0
* Tokenizers 0.12.1
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: 5100 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1+cu116
* Datasets 2.4.0
* Tokenizers 0.12.1
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: 5100### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1+cu116
* Datasets 2.4.0
* Tokenizers 0.12.1