---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-IEMOCAP_4
  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_4

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: 1.3971
- Accuracy: 0.2747

## 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: 4490

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3364        | 0.1   | 450  | 1.4142          | 0.2882   |
| 1.3951        | 1.1   | 900  | 1.3692          | 0.3058   |
| 1.2918        | 2.1   | 1350 | 1.3544          | 0.3357   |
| 1.2283        | 3.1   | 1800 | 1.3673          | 0.3298   |
| 1.2638        | 4.1   | 2250 | 1.3652          | 0.3404   |
| 1.2674        | 5.1   | 2700 | 1.3265          | 0.3538   |
| 1.2737        | 6.1   | 3150 | 1.3092          | 0.3802   |
| 1.1625        | 7.1   | 3600 | 1.2969          | 0.3884   |
| 1.35          | 8.1   | 4050 | 1.3067          | 0.3726   |
| 1.1373        | 9.1   | 4490 | 1.2835          | 0.3972   |


### Framework versions

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