---
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-multiclass-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-multiclass-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: 0.7974
- F1: 0.8701
- Accuracy: 0.8701

## 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     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|
| 1.3802        | 0.04  | 2000  | 1.2381          | 0.52   | 0.52     |
| 1.0115        | 1.04  | 4000  | 1.0522          | 0.6684 | 0.6684   |
| 0.9749        | 2.04  | 6000  | 0.9298          | 0.7537 | 0.7537   |
| 0.9048        | 3.04  | 8000  | 0.8679          | 0.7863 | 0.7863   |
| 0.7977        | 4.04  | 10000 | 0.8846          | 0.7811 | 0.7811   |
| 0.9259        | 5.04  | 12000 | 0.8018          | 0.8263 | 0.8263   |
| 0.6077        | 6.04  | 14000 | 0.8212          | 0.8189 | 0.8189   |
| 0.7102        | 7.04  | 16000 | 0.7876          | 0.8242 | 0.8242   |
| 0.5726        | 8.04  | 18000 | 0.8805          | 0.8232 | 0.8232   |
| 0.7768        | 9.04  | 20000 | 0.7490          | 0.8589 | 0.8589   |
| 0.6793        | 10.04 | 22000 | 0.7730          | 0.8558 | 0.8558   |
| 0.5765        | 11.04 | 24000 | 0.7752          | 0.8368 | 0.8368   |
| 0.4789        | 12.04 | 26000 | 0.7902          | 0.8484 | 0.8484   |
| 0.7398        | 13.04 | 28000 | 0.7603          | 0.8568 | 0.8568   |
| 0.6807        | 14.04 | 30000 | 0.7531          | 0.8716 | 0.8716   |
| 0.3262        | 15.04 | 32000 | 0.7663          | 0.8768 | 0.8768   |
| 0.4387        | 16.04 | 34000 | 0.7549          | 0.88   | 0.88     |
| 0.5013        | 17.04 | 36000 | 0.7713          | 0.8737 | 0.8737   |
| 0.9572        | 18.04 | 38000 | 0.7613          | 0.8684 | 0.8684   |
| 1.0645        | 19.04 | 40000 | 0.7618          | 0.8811 | 0.8811   |
| 0.4949        | 20.04 | 42000 | 0.7882          | 0.8747 | 0.8747   |
| 0.6131        | 21.04 | 44000 | 0.7964          | 0.8705 | 0.8705   |
| 0.628         | 22.04 | 46000 | 0.8089          | 0.8747 | 0.8747   |
| 0.5693        | 23.04 | 48000 | 0.8010          | 0.8747 | 0.8747   |
| 0.4764        | 24.04 | 50000 | 0.8117          | 0.8789 | 0.8789   |


### Framework versions

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