---
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-NOSTRO-Nuovo-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-NOSTRO-Nuovo-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: 2.5911
- Accuracy: 0.1585

## 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: 0.005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 448

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.8766        | 0.3125 | 140  | 2.7276          | 0.0625   |
| 2.719         | 1.3125 | 280  | 2.6597          | 0.0938   |
| 2.6488        | 2.3125 | 420  | 2.6379          | 0.0938   |
| 2.573         | 3.0625 | 448  | 2.6363          | 0.0938   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.0.1+cu117
- Datasets 3.2.0
- Tokenizers 0.21.0