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---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-lift-data-resize
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-lift-data-resize
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: 0.9940
- Accuracy: 0.5408
## 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: 76
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.5445 | 0.2632 | 20 | 1.6095 | 0.1123 |
| 1.2942 | 1.2632 | 40 | 1.2199 | 0.5120 |
| 1.2008 | 2.2632 | 60 | 1.1847 | 0.5267 |
| 1.0759 | 3.2105 | 76 | 1.0455 | 0.5525 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.1.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1
|