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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-short-finetuned-ssv2-finetuned-rwf2000-epochs8-batch8-fp16
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-short-finetuned-ssv2-finetuned-rwf2000-epochs8-batch8-fp16
This model is a fine-tuned version of [MCG-NJU/videomae-base-short-finetuned-ssv2](https://huggingface.co/MCG-NJU/videomae-base-short-finetuned-ssv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4339
- Accuracy: 0.4643
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4239 | 0.06 | 200 | 0.3879 | 0.82 |
| 0.4179 | 1.06 | 400 | 1.1635 | 0.6162 |
| 0.4329 | 2.06 | 600 | 0.8215 | 0.63 |
| 0.3051 | 3.06 | 800 | 0.5541 | 0.7412 |
| 0.172 | 4.06 | 1000 | 0.4696 | 0.8363 |
| 0.1955 | 5.06 | 1200 | 0.5384 | 0.78 |
| 0.2301 | 6.06 | 1400 | 1.3358 | 0.635 |
| 0.2995 | 7.06 | 1600 | 1.0372 | 0.7087 |
| 0.3789 | 8.06 | 1800 | 0.8670 | 0.7412 |
| 0.2525 | 9.06 | 2000 | 0.5886 | 0.8225 |
| 0.1846 | 10.06 | 2200 | 0.7851 | 0.735 |
| 0.1547 | 11.06 | 2400 | 0.8905 | 0.7638 |
| 0.2501 | 12.06 | 2600 | 0.9807 | 0.76 |
| 0.1046 | 13.06 | 2800 | 1.0419 | 0.7438 |
| 0.0786 | 14.06 | 3000 | 1.0128 | 0.7538 |
| 0.0178 | 15.06 | 3200 | 1.0156 | 0.75 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
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