---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-test-small-aug-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-test-small-aug-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: 0.7786
- 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: 8
- eval_batch_size: 8
- 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: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.12  | 2    | 1.3221          | 0.5      |
| No log        | 1.12  | 4    | 1.1049          | 0.5      |
| No log        | 2.12  | 6    | 0.9825          | 0.5      |
| No log        | 3.12  | 8    | 0.8929          | 0.75     |
| 1.2166        | 4.12  | 10   | 0.8538          | 0.5      |
| 1.2166        | 5.12  | 12   | 0.8157          | 0.5      |
| 1.2166        | 6.12  | 14   | 0.7909          | 1.0      |
| 1.2166        | 7.12  | 16   | 0.7786          | 1.0      |


### Framework versions

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