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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-ucf101-subset
  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-ucf101-subset

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: 1.1903
- Accuracy: 0.7335

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1920
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5817        | 0.1255 | 241  | 0.6961          | 0.6601   |
| 0.4524        | 1.1255 | 482  | 1.1878          | 0.6009   |
| 0.5473        | 2.1255 | 723  | 1.0509          | 0.6420   |
| 0.5044        | 3.1255 | 964  | 1.0045          | 0.6745   |
| 0.7258        | 4.1255 | 1205 | 0.9840          | 0.6567   |
| 0.3606        | 5.1255 | 1446 | 1.0898          | 0.7377   |
| 0.2423        | 6.1255 | 1687 | 1.0520          | 0.7460   |
| 0.3488        | 7.1214 | 1920 | 1.1903          | 0.7335   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3