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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-sample_kine
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-sample_kine
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: 0.5079
- Accuracy: 0.8205
## 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: 8
- eval_batch_size: 8
- 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: 140
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7564 | 0.1071 | 15 | 0.6660 | 0.6923 |
| 0.6614 | 1.1071 | 30 | 0.5677 | 0.6923 |
| 0.5941 | 2.1071 | 45 | 0.5079 | 0.8205 |
| 0.3661 | 3.1071 | 60 | 0.6175 | 0.6923 |
| 0.3258 | 4.1071 | 75 | 1.1649 | 0.7436 |
| 0.5887 | 5.1071 | 90 | 0.4697 | 0.7179 |
| 0.3907 | 6.1071 | 105 | 0.9874 | 0.6154 |
| 0.1948 | 7.1071 | 120 | 0.9959 | 0.6667 |
| 0.1424 | 8.1071 | 135 | 1.1357 | 0.6667 |
| 0.2198 | 9.0357 | 140 | 1.1467 | 0.6667 |
### Framework versions
- Transformers 4.43.4
- Pytorch 2.4.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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