---
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: 0.4622
- Accuracy: 0.975

## 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: 960

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8796        | 0.06  | 60   | 3.6666          | 0.05     |
| 3.8535        | 1.06  | 120  | 3.4913          | 0.05     |
| 3.7537        | 2.06  | 180  | 3.3941          | 0.075    |
| 3.5163        | 3.06  | 240  | 3.3433          | 0.075    |
| 3.4903        | 4.06  | 300  | 3.2711          | 0.075    |
| 3.4318        | 5.06  | 360  | 3.2221          | 0.1      |
| 3.0782        | 6.06  | 420  | 3.1301          | 0.225    |
| 3.3261        | 7.06  | 480  | 2.9363          | 0.475    |
| 2.8341        | 8.06  | 540  | 2.5592          | 0.5      |
| 2.4863        | 9.06  | 600  | 1.8678          | 0.8      |
| 1.7275        | 10.06 | 660  | 1.2153          | 0.925    |
| 1.2468        | 11.06 | 720  | 0.9454          | 0.95     |
| 0.871         | 12.06 | 780  | 0.7030          | 0.975    |
| 0.6857        | 13.06 | 840  | 0.5486          | 0.95     |
| 0.6182        | 14.06 | 900  | 0.4743          | 1.0      |
| 0.3517        | 15.06 | 960  | 0.4622          | 0.975    |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3