---
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-v4
  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-v4

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: 1.2089
- 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: 65

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.06  | 4    | 1.8526          | 0.1304   |
| No log        | 1.06  | 8    | 1.6872          | 0.3913   |
| 1.6209        | 2.06  | 12   | 1.4251          | 0.5652   |
| 1.6209        | 3.06  | 16   | 1.2785          | 0.5652   |
| 1.1184        | 4.06  | 20   | 1.1813          | 0.6522   |
| 1.1184        | 5.06  | 24   | 1.0827          | 0.4783   |
| 1.1184        | 6.06  | 28   | 0.9423          | 0.6522   |
| 1.0086        | 7.06  | 32   | 0.9538          | 0.6522   |
| 1.0086        | 8.06  | 36   | 0.8784          | 0.6087   |
| 0.7591        | 9.06  | 40   | 0.9870          | 0.6087   |
| 0.7591        | 10.06 | 44   | 0.9913          | 0.6522   |
| 0.7591        | 11.06 | 48   | 0.8661          | 0.6087   |
| 0.6925        | 12.06 | 52   | 0.8789          | 0.5652   |
| 0.6925        | 13.06 | 56   | 0.8263          | 0.6522   |
| 0.7497        | 14.06 | 60   | 1.0772          | 0.6522   |
| 0.7497        | 15.06 | 64   | 0.9689          | 0.6522   |
| 0.7497        | 16.02 | 65   | 0.8805          | 0.6522   |


### Framework versions

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