NerfLongshot
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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-sign-subset
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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-sign-subset
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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: 3.3672
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- Accuracy: 0.1905
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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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- training_steps: 270
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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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| No log | 0.04 | 11 | 2.4220 | 0.0870 |
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| 2.3491 | 1.04 | 22 | 2.6315 | 0.0 |
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| 2.3491 | 2.04 | 33 | 2.6680 | 0.0435 |
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| 2.2285 | 3.04 | 44 | 2.8487 | 0.1304 |
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| 2.2285 | 4.04 | 55 | 3.0361 | 0.0870 |
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| 1.996 | 5.04 | 66 | 3.0258 | 0.1304 |
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| 1.996 | 6.04 | 77 | 3.2125 | 0.1304 |
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| 1.6956 | 7.04 | 88 | 3.2063 | 0.1304 |
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| 1.6956 | 8.04 | 99 | 3.1919 | 0.1304 |
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| 1.5088 | 9.04 | 110 | 3.1940 | 0.1304 |
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| 1.3777 | 10.04 | 121 | 3.3180 | 0.1739 |
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| 1.3777 | 11.04 | 132 | 3.3112 | 0.1304 |
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| 1.1509 | 12.04 | 143 | 3.3400 | 0.1304 |
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| 1.1509 | 13.04 | 154 | 3.2550 | 0.1739 |
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| 0.9036 | 14.04 | 165 | 3.3682 | 0.1304 |
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| 0.9036 | 15.04 | 176 | 3.3775 | 0.1304 |
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| 0.8303 | 16.04 | 187 | 3.4701 | 0.1304 |
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| 0.8303 | 17.04 | 198 | 3.4340 | 0.1739 |
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| 0.6683 | 18.04 | 209 | 3.4843 | 0.1304 |
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| 0.5126 | 19.04 | 220 | 3.3552 | 0.2174 |
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| 0.5126 | 20.04 | 231 | 3.3702 | 0.2609 |
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| 0.3728 | 21.04 | 242 | 3.3871 | 0.2609 |
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| 0.3728 | 22.04 | 253 | 3.3565 | 0.2609 |
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| 0.3291 | 23.04 | 264 | 3.3861 | 0.3043 |
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| 0.3291 | 24.02 | 270 | 3.3876 | 0.3043 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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