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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-ucf101-subset-diagnose
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-ucf101-subset-diagnose
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: 0.8572
- Accuracy: 0.5573
## 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: 4
- eval_batch_size: 4
- 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: 850
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8885 | 0.1012 | 86 | 1.0729 | 0.3385 |
| 0.9537 | 1.1012 | 172 | 0.9109 | 0.4120 |
| 0.9089 | 2.1012 | 258 | 1.0296 | 0.2957 |
| 1.0412 | 3.1012 | 344 | 1.1838 | 0.2991 |
| 0.8928 | 4.1012 | 430 | 0.7726 | 0.6154 |
| 0.7793 | 5.1012 | 516 | 0.7928 | 0.6444 |
| 0.8378 | 6.1012 | 602 | 0.9475 | 0.5248 |
| 0.7738 | 7.1012 | 688 | 0.9032 | 0.5504 |
| 0.6334 | 8.1012 | 774 | 0.9769 | 0.5385 |
| 0.4142 | 9.0894 | 850 | 0.8572 | 0.5573 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
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