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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: MCG-NJU/videomae-base-finetuned-kinetics
model-index:
- name: videomae-base-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-kb
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-kinetics-finetuned-rwf2000-epochs8-batch8-kb
This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5482
- Accuracy: 0.7298
## 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4492 | 0.06 | 200 | 0.2361 | 0.905 |
| 0.3517 | 1.06 | 400 | 0.5648 | 0.8137 |
| 0.2255 | 2.06 | 600 | 0.7592 | 0.7575 |
| 0.1983 | 3.06 | 800 | 0.4803 | 0.835 |
| 0.2305 | 4.06 | 1000 | 0.4290 | 0.8738 |
| 0.1276 | 5.06 | 1200 | 0.4317 | 0.8762 |
| 0.1597 | 6.06 | 1400 | 1.3708 | 0.6937 |
| 0.3088 | 7.06 | 1600 | 0.3974 | 0.8862 |
| 0.2687 | 8.06 | 1800 | 0.5986 | 0.85 |
| 0.2085 | 9.06 | 2000 | 0.4264 | 0.8862 |
| 0.1338 | 10.06 | 2200 | 0.5015 | 0.8675 |
| 0.2191 | 11.06 | 2400 | 0.7103 | 0.845 |
| 0.2255 | 12.06 | 2600 | 0.4939 | 0.8762 |
| 0.0298 | 13.06 | 2800 | 0.6338 | 0.8612 |
| 0.0687 | 14.06 | 3000 | 0.5350 | 0.8738 |
| 0.0146 | 15.06 | 3200 | 0.4770 | 0.8838 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
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