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---
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
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