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---
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
|