---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-IEMOCAP_2
  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_2

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: 1.3381
- Accuracy: 0.3434

## 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: 4500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3215        | 0.1   | 451  | 1.4351          | 0.2622   |
| 1.3236        | 1.1   | 902  | 1.3517          | 0.3579   |
| 1.2642        | 2.1   | 1353 | 1.4280          | 0.2982   |
| 1.2741        | 3.1   | 1804 | 1.3943          | 0.3012   |
| 1.2655        | 4.1   | 2255 | 1.3665          | 0.3311   |
| 1.1476        | 5.1   | 2706 | 1.3808          | 0.3293   |
| 1.2231        | 6.1   | 3157 | 1.3216          | 0.3573   |
| 1.2715        | 7.1   | 3608 | 1.3162          | 0.3720   |
| 1.3088        | 8.1   | 4059 | 1.2985          | 0.3982   |
| 1.2636        | 9.1   | 4500 | 1.2666          | 0.4098   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3