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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: videomae-base-finetuned-elderf1
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-elderf1
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: 1.7031
- Accuracy: 0.3481
## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 720
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7358 | 0.1 | 73 | 1.6923 | 0.3408 |
| 1.7163 | 1.1 | 146 | 1.6662 | 0.3373 |
| 1.7018 | 2.1 | 219 | 1.6378 | 0.3408 |
| 1.7334 | 3.1 | 292 | 1.6563 | 0.3401 |
| 1.672 | 4.1 | 365 | 1.6568 | 0.2398 |
| 1.7095 | 5.1 | 438 | 1.6313 | 0.3387 |
| 1.7119 | 6.1 | 511 | 1.6309 | 0.3408 |
| 1.6981 | 7.1 | 584 | 1.6518 | 0.3289 |
| 1.7066 | 8.1 | 657 | 1.6313 | 0.3310 |
| 1.6476 | 9.09 | 720 | 1.6338 | 0.3289 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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