---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-groub29-30-finetuned-SLT-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-groub29-30-finetuned-SLT-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: 2.8812
- Accuracy: 0.1111

## 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: 4
- eval_batch_size: 4
- 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: 48

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.15  | 7    | 3.2525          | 0.0741   |
| 3.4041        | 1.15  | 14   | 3.1928          | 0.0741   |
| 3.3195        | 2.15  | 21   | 3.0810          | 0.1111   |
| 3.3195        | 3.15  | 28   | 3.0070          | 0.1111   |
| 3.1425        | 4.15  | 35   | 2.9406          | 0.1481   |
| 2.9592        | 5.15  | 42   | 2.8942          | 0.1481   |
| 2.9592        | 6.12  | 48   | 2.8812          | 0.1111   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3