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

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: 1.3290
- Accuracy: 0.3497

## 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: 4070

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.4698        | 0.1002 | 408  | 1.4911          | 0.2071   |
| 1.396         | 1.1002 | 816  | 1.3825          | 0.2621   |
| 1.2776        | 2.1002 | 1224 | 1.4461          | 0.2714   |
| 1.2976        | 3.1002 | 1632 | 1.4535          | 0.2632   |
| 1.34          | 4.1002 | 2040 | 1.4480          | 0.2527   |
| 1.3607        | 5.1002 | 2448 | 1.3579          | 0.3121   |
| 1.2931        | 6.1002 | 2856 | 1.3612          | 0.3159   |
| 1.3231        | 7.1002 | 3264 | 1.3727          | 0.2582   |
| 1.3491        | 8.1002 | 3672 | 1.4132          | 0.2451   |
| 1.2063        | 9.0978 | 4070 | 1.4588          | 0.2582   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1