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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-large-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-kl-torch2
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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-large-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-kl-torch2
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This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6146
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- Accuracy: 0.7212
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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: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 8
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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: 3200
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- mixed_precision_training: Native AMP
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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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| 0.361 | 0.06 | 200 | 0.2425 | 0.895 |
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| 0.3449 | 1.06 | 400 | 0.6639 | 0.68 |
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| 0.2435 | 2.06 | 600 | 0.9180 | 0.6663 |
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| 0.2001 | 3.06 | 800 | 0.5656 | 0.7662 |
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| 0.1405 | 4.06 | 1000 | 0.3859 | 0.86 |
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| 0.1845 | 5.06 | 1200 | 0.3825 | 0.8675 |
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| 0.1586 | 6.06 | 1400 | 1.4446 | 0.6687 |
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| 0.2013 | 7.06 | 1600 | 0.4730 | 0.8562 |
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| 0.2113 | 8.06 | 1800 | 0.3328 | 0.8862 |
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| 0.245 | 9.06 | 2000 | 0.3519 | 0.8938 |
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| 0.1767 | 10.06 | 2200 | 0.4004 | 0.895 |
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| 0.1688 | 11.06 | 2400 | 0.6468 | 0.86 |
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| 0.2823 | 12.06 | 2600 | 0.6006 | 0.8575 |
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| 0.0928 | 13.06 | 2800 | 0.5516 | 0.875 |
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| 0.0079 | 14.06 | 3000 | 0.5855 | 0.87 |
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| 0.0325 | 15.06 | 3200 | 0.4921 | 0.8925 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0+cu117
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- Datasets 2.11.0
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- Tokenizers 0.13.2
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