---
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: 0.3217
- 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: 960

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9388        | 0.06  | 61   | 3.6928          | 0.0244   |
| 3.922         | 1.06  | 122  | 3.7470          | 0.0244   |
| 3.8564        | 2.06  | 183  | 3.5744          | 0.0488   |
| 3.8           | 3.06  | 244  | 3.4795          | 0.0732   |
| 3.6299        | 4.06  | 305  | 3.4226          | 0.0732   |
| 3.7411        | 5.06  | 366  | 3.3728          | 0.0732   |
| 3.4738        | 6.06  | 427  | 3.2456          | 0.0732   |
| 3.3784        | 7.06  | 488  | 2.8674          | 0.5610   |
| 2.9917        | 8.06  | 549  | 2.2194          | 0.7073   |
| 2.1432        | 9.06  | 610  | 1.4439          | 0.8780   |
| 1.377         | 10.06 | 671  | 1.0637          | 0.9512   |
| 1.1721        | 11.06 | 732  | 0.7384          | 0.9512   |
| 0.8749        | 12.06 | 793  | 0.4955          | 1.0      |
| 0.4729        | 13.06 | 854  | 0.3995          | 1.0      |
| 0.4317        | 14.06 | 915  | 0.3367          | 1.0      |
| 0.3025        | 15.05 | 960  | 0.3217          | 1.0      |


### Framework versions

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