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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_5
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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_5
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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: 1.3229
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- Accuracy: 0.3770
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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: 4280
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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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| 1.3642 | 0.1 | 429 | 1.4078 | 0.1970 |
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| 1.3244 | 1.1 | 858 | 1.4578 | 0.3052 |
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| 1.3623 | 2.1 | 1287 | 1.4071 | 0.2314 |
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| 1.3422 | 3.1 | 1716 | 1.3474 | 0.2896 |
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| 1.2483 | 4.1 | 2145 | 1.3597 | 0.3127 |
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| 1.3581 | 5.1 | 2574 | 1.3512 | 0.2639 |
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| 1.3106 | 6.1 | 3003 | 1.3295 | 0.2896 |
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| 1.341 | 7.1 | 3432 | 1.3132 | 0.3433 |
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| 1.2438 | 8.1 | 3861 | 1.2732 | 0.3859 |
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| 1.2438 | 9.1 | 4280 | 1.2643 | 0.3715 |
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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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