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---
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-finetuned-rwf2000-subset___v1
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-finetuned-rwf2000-subset___v1
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: 0.4808
- Accuracy: 0.775
## 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: 1e-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: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5205 | 0.2 | 100 | 0.5434 | 0.6837 |
| 0.4084 | 1.2 | 200 | 0.5905 | 0.655 |
| 0.4198 | 2.2 | 300 | 0.4814 | 0.7462 |
| 0.3188 | 3.2 | 400 | 0.5160 | 0.755 |
| 0.2687 | 4.2 | 500 | 0.4808 | 0.775 |
### Framework versions
- Transformers 4.46.2
- Pytorch 1.13.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.3
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