transformers safetensors videomae video-classification generated_from_trainer base_model:minhah/videomae-base-finetuned-ucf101-subset license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: minhah/videomae-base-finetuned-ucf101-subset
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-subset-finetuned-elder-UFC-prtuned
  results: []
---

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# videomae-base-finetuned-ucf101-subset-finetuned-elder-UFC-prtuned

This model is a fine-tuned version of [minhah/videomae-base-finetuned-ucf101-subset](https://huggingface.co/minhah/videomae-base-finetuned-ucf101-subset) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6593
- Accuracy: 0.3481

## 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: 576

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.729         | 0.13  | 73   | 1.6346          | 0.3408   |
| 1.683         | 1.13  | 146  | 1.6505          | 0.3029   |
| 1.6889        | 2.13  | 219  | 1.6359          | 0.3408   |
| 1.6853        | 3.13  | 292  | 1.6739          | 0.2398   |
| 1.5793        | 4.13  | 365  | 1.6679          | 0.2588   |
| 1.5783        | 5.13  | 438  | 1.6091          | 0.3324   |
| 1.5745        | 6.13  | 511  | 1.6306          | 0.3072   |
| 1.5704        | 7.11  | 576  | 1.6573          | 0.2707   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
