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README.md
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---
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license: cc-by-nc-4.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: videomae-base-finetuned-IEMOCAP_3
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# videomae-base-finetuned-IEMOCAP_3
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This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3701
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- Accuracy: 0.3179
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 4370
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.3648 | 0.1 | 438 | 1.3661 | 0.3746 |
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| 1.3188 | 1.1 | 876 | 1.3436 | 0.3215 |
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| 1.2826 | 2.1 | 1314 | 1.3651 | 0.3215 |
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| 1.2141 | 3.1 | 1752 | 1.3170 | 0.3759 |
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| 1.2555 | 4.1 | 2190 | 1.3018 | 0.4053 |
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| 1.2422 | 5.1 | 2628 | 1.3036 | 0.3565 |
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| 1.2776 | 6.1 | 3066 | 1.2650 | 0.3921 |
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| 1.2074 | 7.1 | 3504 | 1.2655 | 0.3971 |
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| 1.2354 | 8.1 | 3942 | 1.2542 | 0.3952 |
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| 1.0865 | 9.1 | 4370 | 1.2498 | 0.4078 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.0
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- Tokenizers 0.13.3
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