---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-kinetics-0408_final_5sec_org_ab7_val_as123
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# videomae-base-finetuned-kinetics-0408_final_5sec_org_ab7_val_as123

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: 0.3219
- Accuracy: 0.9225

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 65800

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 0.537         | 0.0100  | 659   | 0.3567          | 0.8740   |
| 0.0105        | 1.0100  | 1318  | 0.2819          | 0.9139   |
| 0.0039        | 2.0100  | 1977  | 0.3886          | 0.8858   |
| 0.0023        | 3.0100  | 2636  | 0.7164          | 0.8169   |
| 0.0222        | 4.0100  | 3295  | 0.2866          | 0.9264   |
| 0.0076        | 5.0100  | 3954  | 0.4126          | 0.9006   |
| 1.008         | 6.0100  | 4613  | 0.3480          | 0.9006   |
| 0.2086        | 7.0100  | 5272  | 0.2673          | 0.9311   |
| 0.4466        | 8.0100  | 5931  | 0.3282          | 0.9264   |
| 0.0067        | 9.0100  | 6590  | 0.3301          | 0.9116   |
| 1.3353        | 10.0100 | 7249  | 0.5289          | 0.8654   |
| 0.0003        | 11.0100 | 7908  | 0.6538          | 0.8732   |
| 0.0003        | 12.0100 | 8567  | 0.3669          | 0.9241   |
| 0.0184        | 13.0100 | 9226  | 0.3609          | 0.9171   |
| 0.0002        | 14.0100 | 9885  | 0.5037          | 0.8975   |
| 0.0001        | 15.0100 | 10544 | 0.4052          | 0.9202   |
| 0.0077        | 16.0100 | 11203 | 0.5142          | 0.9014   |
| 0.0001        | 17.0100 | 11862 | 0.3801          | 0.9241   |
| 0.0092        | 18.0100 | 12521 | 0.5826          | 0.9030   |
| 0.0012        | 19.0100 | 13180 | 0.4868          | 0.9155   |
| 0.0043        | 20.0100 | 13839 | 0.4497          | 0.9186   |
| 0.0001        | 21.0100 | 14498 | 0.7081          | 0.8858   |
| 0.0           | 22.0100 | 15157 | 0.8394          | 0.8725   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0