---
license: cc-by-nc-4.0
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: 1.3194
- Accuracy: 0.3761

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4161        | 0.1   | 408  | 1.4228          | 0.2115   |
| 1.3522        | 1.1   | 816  | 1.3968          | 0.2363   |
| 1.2575        | 2.1   | 1224 | 1.4228          | 0.3115   |
| 1.2897        | 3.1   | 1632 | 1.4101          | 0.2984   |
| 1.3398        | 4.1   | 2040 | 1.4176          | 0.2599   |
| 1.3621        | 5.1   | 2448 | 1.3590          | 0.2830   |
| 1.2824        | 6.1   | 2856 | 1.3133          | 0.3610   |
| 1.3064        | 7.1   | 3264 | 1.3195          | 0.3077   |
| 1.378         | 8.1   | 3672 | 1.3562          | 0.2643   |
| 1.1909        | 9.1   | 4070 | 1.3917          | 0.2621   |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3