---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: VideoMAE_Base_wlasl_100_longtail_200
  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_Base_wlasl_100_longtail_200

This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9736
- Accuracy: 0.4822

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 0.1
- training_steps: 36000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 18.7021       | 0.005   | 180  | 4.6442          | 0.0118   |
| 18.6026       | 1.0050  | 360  | 4.6319          | 0.0118   |
| 18.5393       | 2.0050  | 540  | 4.6238          | 0.0178   |
| 18.3789       | 3.0050  | 721  | 4.6170          | 0.0178   |
| 18.3763       | 4.005   | 901  | 4.6237          | 0.0178   |
| 18.334        | 5.0050  | 1081 | 4.6342          | 0.0296   |
| 18.1779       | 6.0050  | 1261 | 4.6036          | 0.0296   |
| 17.9948       | 7.0050  | 1442 | 4.5903          | 0.0266   |
| 17.9333       | 8.005   | 1622 | 4.6144          | 0.0237   |
| 17.7505       | 9.0050  | 1802 | 4.5865          | 0.0118   |
| 17.4917       | 10.0050 | 1982 | 4.5626          | 0.0207   |
| 16.9821       | 11.0050 | 2163 | 4.3615          | 0.0444   |
| 16.2362       | 12.005  | 2343 | 4.1515          | 0.0533   |
| 15.2255       | 13.0050 | 2523 | 3.9603          | 0.0740   |
| 14.0646       | 14.0050 | 2703 | 3.7594          | 0.0828   |
| 12.8642       | 15.0050 | 2884 | 3.4154          | 0.1420   |
| 11.6502       | 16.005  | 3064 | 3.3917          | 0.1627   |
| 10.332        | 17.0050 | 3244 | 3.0359          | 0.2249   |
| 8.9465        | 18.0050 | 3424 | 2.8625          | 0.2840   |
| 7.6629        | 19.0050 | 3605 | 2.8202          | 0.3107   |
| 6.2517        | 20.005  | 3785 | 2.6478          | 0.3343   |
| 5.1876        | 21.0050 | 3965 | 2.4982          | 0.3728   |
| 4.0929        | 22.0050 | 4145 | 2.3891          | 0.3876   |
| 3.0425        | 23.0050 | 4326 | 2.2212          | 0.4083   |
| 2.3667        | 24.005  | 4506 | 2.1609          | 0.4586   |
| 1.7821        | 25.0050 | 4686 | 2.2471          | 0.4260   |
| 1.4215        | 26.0050 | 4866 | 2.2263          | 0.4675   |
| 1.1324        | 27.0050 | 5047 | 2.2360          | 0.4556   |
| 0.9114        | 28.005  | 5227 | 2.2021          | 0.4852   |
| 0.6966        | 29.0050 | 5407 | 2.3123          | 0.4408   |
| 0.5676        | 30.0050 | 5587 | 2.1198          | 0.5355   |
| 0.4494        | 31.0050 | 5768 | 2.2495          | 0.4911   |
| 0.3321        | 32.005  | 5948 | 2.2658          | 0.5089   |
| 0.227         | 33.0050 | 6128 | 2.4423          | 0.4882   |
| 0.2203        | 34.0050 | 6308 | 2.4358          | 0.4763   |
| 0.2643        | 35.0050 | 6489 | 2.5521          | 0.4675   |
| 0.111         | 36.005  | 6669 | 2.5787          | 0.4882   |
| 0.1009        | 37.0050 | 6849 | 2.4022          | 0.5059   |
| 0.1275        | 38.0050 | 7029 | 2.5451          | 0.5      |
| 0.1874        | 39.0050 | 7210 | 2.8339          | 0.4586   |
| 0.1695        | 40.005  | 7390 | 3.0320          | 0.4320   |
| 0.1735        | 41.0050 | 7570 | 2.6961          | 0.4941   |
| 0.1299        | 42.0050 | 7750 | 2.9589          | 0.4675   |
| 0.1399        | 43.0050 | 7931 | 2.6799          | 0.5325   |
| 0.118         | 44.005  | 8111 | 2.8731          | 0.5      |
| 0.1583        | 45.0050 | 8291 | 2.8757          | 0.4970   |
| 0.1667        | 46.0050 | 8471 | 2.9294          | 0.4941   |
| 0.202         | 47.0050 | 8652 | 3.1443          | 0.4615   |
| 0.1301        | 48.005  | 8832 | 2.8941          | 0.5207   |
| 0.2298        | 49.0050 | 9012 | 3.1270          | 0.4704   |
| 0.1858        | 50.0050 | 9192 | 2.9736          | 0.4822   |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1