---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-IEMOCAP_3
  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_3

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: 1.3701
- Accuracy: 0.3179

## 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: 4370

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3648        | 0.1   | 438  | 1.3661          | 0.3746   |
| 1.3188        | 1.1   | 876  | 1.3436          | 0.3215   |
| 1.2826        | 2.1   | 1314 | 1.3651          | 0.3215   |
| 1.2141        | 3.1   | 1752 | 1.3170          | 0.3759   |
| 1.2555        | 4.1   | 2190 | 1.3018          | 0.4053   |
| 1.2422        | 5.1   | 2628 | 1.3036          | 0.3565   |
| 1.2776        | 6.1   | 3066 | 1.2650          | 0.3921   |
| 1.2074        | 7.1   | 3504 | 1.2655          | 0.3971   |
| 1.2354        | 8.1   | 3942 | 1.2542          | 0.3952   |
| 1.0865        | 9.1   | 4370 | 1.2498          | 0.4078   |


### Framework versions

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