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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-ElderReact-anger-balanced-hp
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-ElderReact-anger-balanced-hp
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: 0.6938
- Accuracy: 0.4672
## 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: 480
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7532 | 0.05 | 25 | 0.7078 | 0.5238 |
| 0.7571 | 1.05 | 50 | 0.7034 | 0.4762 |
| 0.7357 | 2.05 | 75 | 0.7080 | 0.4429 |
| 0.6976 | 3.05 | 100 | 0.7160 | 0.5238 |
| 0.7131 | 4.05 | 125 | 0.6893 | 0.4714 |
| 0.7275 | 5.05 | 150 | 0.8350 | 0.4929 |
| 0.7334 | 6.05 | 175 | 0.7127 | 0.4738 |
| 0.7274 | 7.05 | 200 | 0.7088 | 0.5048 |
| 0.697 | 8.05 | 225 | 0.6911 | 0.5190 |
| 0.7605 | 9.05 | 250 | 0.7296 | 0.4976 |
| 0.7105 | 10.05 | 275 | 0.7100 | 0.4833 |
| 0.6745 | 11.05 | 300 | 0.7271 | 0.4548 |
| 0.7166 | 12.05 | 325 | 0.6955 | 0.5286 |
| 0.6849 | 13.05 | 350 | 0.6981 | 0.4976 |
| 0.6978 | 14.05 | 375 | 0.6976 | 0.4952 |
| 0.6928 | 15.05 | 400 | 0.6941 | 0.5405 |
| 0.7057 | 16.05 | 425 | 0.7022 | 0.5 |
| 0.6842 | 17.05 | 450 | 0.6943 | 0.4738 |
| 0.6824 | 18.05 | 475 | 0.6945 | 0.5167 |
| 0.7065 | 19.01 | 480 | 0.6948 | 0.5143 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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