---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-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-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: 0.4062
- Accuracy: 1.0

## 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: 2
- eval_batch_size: 2
- 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: 944

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8603        | 0.06  | 59   | 3.7147          | 0.025    |
| 3.7747        | 1.06  | 118  | 3.6984          | 0.05     |
| 3.83          | 2.06  | 177  | 3.5418          | 0.075    |
| 3.5065        | 3.06  | 236  | 3.3917          | 0.075    |
| 3.6541        | 4.06  | 295  | 3.3558          | 0.1      |
| 3.5419        | 5.06  | 354  | 3.2460          | 0.15     |
| 3.2664        | 6.06  | 413  | 3.0603          | 0.2      |
| 3.2295        | 7.06  | 472  | 2.7967          | 0.425    |
| 2.829         | 8.06  | 531  | 2.3743          | 0.625    |
| 2.5769        | 9.06  | 590  | 1.9349          | 0.675    |
| 2.0383        | 10.06 | 649  | 1.3413          | 0.875    |
| 1.8328        | 11.06 | 708  | 0.9239          | 0.925    |
| 1.0447        | 12.06 | 767  | 0.6702          | 0.975    |
| 0.8312        | 13.06 | 826  | 0.5127          | 1.0      |
| 0.7203        | 14.06 | 885  | 0.4366          | 1.0      |
| 0.6204        | 15.06 | 944  | 0.4062          | 1.0      |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0