---
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-cart-activity-v0
  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-cart-activity-v0

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: 0.2626
- Accuracy: 0.9101

## 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: 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: 1272

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4774        | 0.125 | 159  | 0.5977          | 0.7471   |
| 0.2843        | 1.125 | 318  | 0.3505          | 0.8835   |
| 0.2384        | 2.125 | 477  | 0.3886          | 0.8586   |
| 0.2976        | 3.125 | 636  | 0.3410          | 0.8852   |
| 0.2244        | 4.125 | 795  | 0.3221          | 0.8802   |
| 0.2358        | 5.125 | 954  | 0.2995          | 0.8935   |
| 0.2745        | 6.125 | 1113 | 0.2763          | 0.9052   |
| 0.089         | 7.125 | 1272 | 0.2628          | 0.9101   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0