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---
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
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