---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-Accident-MultipleLabels-Video-subset-v2-checkpointing
  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-MultipleLabels-Video-subset-v2-checkpointing

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: 1.7371
- Accuracy: 0.3704

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 35

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.06  | 2    | 1.7265          | 0.3594   |
| No log        | 1.06  | 4    | 1.6976          | 0.3906   |
| No log        | 2.06  | 6    | 1.7503          | 0.3594   |
| No log        | 3.06  | 8    | 1.8831          | 0.3125   |
| 1.7254        | 4.06  | 10   | 2.0285          | 0.1719   |
| 1.7254        | 5.06  | 12   | 2.0391          | 0.2812   |
| 1.7254        | 6.06  | 14   | 1.9737          | 0.3281   |
| 1.7254        | 7.06  | 16   | 1.8998          | 0.375    |
| 1.7254        | 8.06  | 18   | 1.8786          | 0.375    |
| 1.394         | 9.06  | 20   | 1.9054          | 0.3438   |
| 1.394         | 10.06 | 22   | 1.9474          | 0.3281   |
| 1.394         | 11.06 | 24   | 2.0032          | 0.3281   |
| 1.394         | 12.06 | 26   | 2.0729          | 0.3281   |
| 1.394         | 13.06 | 28   | 2.1081          | 0.3438   |
| 1.285         | 14.06 | 30   | 2.1190          | 0.3281   |
| 1.285         | 15.06 | 32   | 2.1188          | 0.3438   |
| 1.285         | 16.06 | 34   | 2.1155          | 0.3594   |
| 1.285         | 17.03 | 35   | 2.1163          | 0.3594   |


### Framework versions

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