---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-Accident-SingleLabel-Final-v2
  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. -->

# finetuned-Accident-SingleLabel-Final-v2

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: 1.2768
- Accuracy: 0.5588

## 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
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.08  | 4    | 1.8602          | 0.1304   |
| No log        | 1.08  | 8    | 1.6211          | 0.4783   |
| 1.7588        | 2.08  | 12   | 1.4450          | 0.5652   |
| 1.7588        | 3.08  | 16   | 1.2476          | 0.6087   |
| 1.0616        | 4.08  | 20   | 1.1461          | 0.6087   |
| 1.0616        | 5.08  | 24   | 1.0131          | 0.5217   |
| 1.0616        | 6.08  | 28   | 0.9023          | 0.6087   |
| 0.9537        | 7.08  | 32   | 0.9932          | 0.6087   |
| 0.9537        | 8.08  | 36   | 0.9547          | 0.6087   |
| 0.7395        | 9.08  | 40   | 1.0174          | 0.6087   |
| 0.7395        | 10.08 | 44   | 0.9636          | 0.6087   |
| 0.7395        | 11.08 | 48   | 0.9022          | 0.5652   |
| 0.7531        | 12.04 | 50   | 0.9311          | 0.5652   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1