---
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: 0.5126
- Accuracy: 0.7586

## 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: 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: 150

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9276        | 0.0933  | 14   | 0.8787          | 0.6207   |
| 0.8845        | 1.0933  | 28   | 0.7380          | 0.7069   |
| 0.685         | 2.0933  | 42   | 0.7084          | 0.7069   |
| 0.7556        | 3.0933  | 56   | 0.6161          | 0.8103   |
| 0.5482        | 4.0933  | 70   | 0.6827          | 0.7414   |
| 0.6461        | 5.0933  | 84   | 0.6916          | 0.7069   |
| 0.701         | 6.0933  | 98   | 0.5490          | 0.8103   |
| 0.5242        | 7.0933  | 112  | 0.5372          | 0.7931   |
| 0.4482        | 8.0933  | 126  | 0.5276          | 0.8103   |
| 0.3898        | 9.0933  | 140  | 0.5047          | 0.7931   |
| 0.3664        | 10.0667 | 150  | 0.5126          | 0.7586   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0