---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: videomae-finetuned-nba-5-class-4-batch-8000-vid-multilabel-4
  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-finetuned-nba-5-class-4-batch-8000-vid-multilabel-4

This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4886
- F1: 0.8863
- Roc Auc: 0.9209
- Accuracy: 0.7962

## 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: 1.5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 50000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.771         | 0.04  | 2000  | 0.7660          | 0.6227 | 0.7324  | 0.2937   |
| 0.6225        | 1.04  | 4000  | 0.6446          | 0.7401 | 0.8162  | 0.4653   |
| 0.6093        | 2.04  | 6000  | 0.6517          | 0.7441 | 0.8223  | 0.5253   |
| 0.603         | 3.04  | 8000  | 0.5630          | 0.8151 | 0.8722  | 0.6558   |
| 0.6547        | 4.04  | 10000 | 0.5009          | 0.8425 | 0.8911  | 0.6695   |
| 0.6426        | 5.04  | 12000 | 0.5179          | 0.8422 | 0.9012  | 0.6642   |
| 0.4447        | 6.04  | 14000 | 0.5052          | 0.8537 | 0.8973  | 0.7147   |
| 0.6949        | 7.04  | 16000 | 0.5045          | 0.8548 | 0.8974  | 0.7337   |
| 0.509         | 8.04  | 18000 | 0.5262          | 0.8705 | 0.9089  | 0.7768   |
| 0.4341        | 9.04  | 20000 | 0.4731          | 0.8831 | 0.9163  | 0.7863   |
| 0.5037        | 10.04 | 22000 | 0.5040          | 0.8781 | 0.9154  | 0.7747   |
| 0.3592        | 11.04 | 24000 | 0.5091          | 0.8746 | 0.9101  | 0.7821   |
| 0.2829        | 12.04 | 26000 | 0.4709          | 0.8867 | 0.9230  | 0.7905   |
| 0.3599        | 13.04 | 28000 | 0.4722          | 0.8888 | 0.9230  | 0.7947   |
| 0.4152        | 14.04 | 30000 | 0.4744          | 0.8911 | 0.9247  | 0.8074   |
| 0.1167        | 15.04 | 32000 | 0.4817          | 0.8949 | 0.9241  | 0.8179   |
| 0.2721        | 16.04 | 34000 | 0.4627          | 0.9064 | 0.9337  | 0.8274   |
| 0.42          | 17.04 | 36000 | 0.4849          | 0.8992 | 0.9282  | 0.8295   |
| 0.5841        | 18.04 | 38000 | 0.4747          | 0.9026 | 0.9304  | 0.8379   |
| 0.509         | 19.04 | 40000 | 0.4779          | 0.8991 | 0.9273  | 0.8316   |
| 0.1599        | 20.04 | 42000 | 0.4945          | 0.9056 | 0.9319  | 0.8411   |
| 0.3645        | 21.04 | 44000 | 0.4875          | 0.8984 | 0.9277  | 0.8242   |
| 0.4402        | 22.04 | 46000 | 0.5156          | 0.9004 | 0.9283  | 0.8368   |
| 0.2769        | 23.04 | 48000 | 0.5063          | 0.9028 | 0.9296  | 0.8389   |
| 0.3009        | 24.04 | 50000 | 0.5122          | 0.8975 | 0.9257  | 0.8326   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1