---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-large-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-large
  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-large

This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5042
- Accuracy: 0.4286

## 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: 16
- eval_batch_size: 16
- 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: 220

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6619        | 0.03  | 7    | 2.7017          | 0.0      |
| 2.6232        | 1.03  | 14   | 2.6628          | 0.0      |
| 2.381         | 2.03  | 21   | 2.5798          | 0.1667   |
| 2.2215        | 3.03  | 28   | 2.4757          | 0.1667   |
| 1.7389        | 4.03  | 35   | 2.3636          | 0.2333   |
| 1.3366        | 5.03  | 42   | 2.2424          | 0.3      |
| 1.1946        | 6.03  | 49   | 2.1675          | 0.3      |
| 0.6809        | 7.03  | 56   | 2.0548          | 0.3667   |
| 0.5255        | 8.03  | 63   | 2.0410          | 0.4      |
| 0.3285        | 9.03  | 70   | 1.9539          | 0.4      |
| 0.2849        | 10.03 | 77   | 1.8536          | 0.4667   |
| 0.1832        | 11.03 | 84   | 1.8293          | 0.4333   |
| 0.1307        | 12.03 | 91   | 1.8200          | 0.4      |
| 0.0901        | 13.03 | 98   | 1.8355          | 0.4      |
| 0.0636        | 14.03 | 105  | 1.8201          | 0.4333   |
| 0.0413        | 15.03 | 112  | 1.7750          | 0.4667   |
| 0.0427        | 16.03 | 119  | 1.7460          | 0.5333   |
| 0.0254        | 17.03 | 126  | 1.7804          | 0.5333   |
| 0.0203        | 18.03 | 133  | 1.8869          | 0.4333   |
| 0.0174        | 19.03 | 140  | 1.7741          | 0.5667   |
| 0.0154        | 20.03 | 147  | 1.7401          | 0.5333   |
| 0.0136        | 21.03 | 154  | 1.7672          | 0.5      |
| 0.0116        | 22.03 | 161  | 1.7793          | 0.5333   |
| 0.0123        | 23.03 | 168  | 1.8018          | 0.4667   |
| 0.0102        | 24.03 | 175  | 1.8024          | 0.5      |
| 0.0103        | 25.03 | 182  | 1.8058          | 0.5      |
| 0.0089        | 26.03 | 189  | 1.8106          | 0.5      |
| 0.0088        | 27.03 | 196  | 1.8029          | 0.5      |
| 0.0092        | 28.03 | 203  | 1.7961          | 0.5      |
| 0.0083        | 29.03 | 210  | 1.7940          | 0.5      |
| 0.0099        | 30.03 | 217  | 1.7922          | 0.5      |
| 0.0085        | 31.01 | 220  | 1.7920          | 0.5      |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2