---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-IEMOCAP_5
  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_5

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: 1.3229
- Accuracy: 0.3770

## 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: 4280

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3642        | 0.1   | 429  | 1.4078          | 0.1970   |
| 1.3244        | 1.1   | 858  | 1.4578          | 0.3052   |
| 1.3623        | 2.1   | 1287 | 1.4071          | 0.2314   |
| 1.3422        | 3.1   | 1716 | 1.3474          | 0.2896   |
| 1.2483        | 4.1   | 2145 | 1.3597          | 0.3127   |
| 1.3581        | 5.1   | 2574 | 1.3512          | 0.2639   |
| 1.3106        | 6.1   | 3003 | 1.3295          | 0.2896   |
| 1.341         | 7.1   | 3432 | 1.3132          | 0.3433   |
| 1.2438        | 8.1   | 3861 | 1.2732          | 0.3859   |
| 1.2438        | 9.1   | 4280 | 1.2643          | 0.3715   |


### Framework versions

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