---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-groub2-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-groub2-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: 0.2405
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.928         | 0.06  | 61   | 3.6624          | 0.0244   |
| 3.8332        | 1.06  | 122  | 3.5354          | 0.0732   |
| 3.5587        | 2.06  | 183  | 3.2996          | 0.0976   |
| 3.4907        | 3.06  | 244  | 3.1796          | 0.0976   |
| 3.4674        | 4.06  | 305  | 3.1159          | 0.0976   |
| 3.5079        | 5.06  | 366  | 3.0202          | 0.1220   |
| 2.9034        | 6.06  | 427  | 2.8292          | 0.1707   |
| 2.9286        | 7.06  | 488  | 2.4582          | 0.6098   |
| 2.4388        | 8.06  | 549  | 1.8469          | 0.7317   |
| 1.7172        | 9.06  | 610  | 1.2915          | 0.8537   |
| 1.2504        | 10.06 | 671  | 0.8991          | 0.9512   |
| 0.974         | 11.06 | 732  | 0.5943          | 0.9268   |
| 0.4528        | 12.06 | 793  | 0.4040          | 0.9512   |
| 0.3593        | 13.06 | 854  | 0.3052          | 1.0      |
| 0.2068        | 14.06 | 915  | 0.2569          | 1.0      |
| 0.185         | 15.05 | 960  | 0.2405          | 1.0      |


### Framework versions

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