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README.md
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license: cc-by-nc-4.0
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---
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license: cc-by-nc-4.0
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base_model: MCG-NJU/videomae-base
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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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- f1
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- precision
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- recall
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model-index:
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- name: videomae-base-finetuned-numbers
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results: []
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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-numbers
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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: 0.3433
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- Accuracy: 0.8222
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- F1: 0.8015
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- Precision: 0.8762
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- Recall: 0.8182
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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: 4
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- eval_batch_size: 4
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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: 176
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.7592 | 0.25 | 44 | 0.6378 | 0.8462 | 0.8479 | 0.8758 | 0.8561 |
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| 0.296 | 1.25 | 88 | 0.3027 | 0.8974 | 0.8805 | 0.9091 | 0.8864 |
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| 0.2144 | 2.25 | 132 | 0.1289 | 0.9487 | 0.9377 | 0.9545 | 0.9394 |
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| 0.1331 | 3.25 | 176 | 0.0958 | 0.9744 | 0.9688 | 0.9773 | 0.9697 |
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### Framework versions
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- Transformers 4.40.0
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- Pytorch 2.1.0+cu121
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- Datasets 2.18.0
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- Tokenizers 0.19.1
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runs/Apr28_03-32-49_blackhorse/events.out.tfevents.1714258486.blackhorse.2381173.4
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version https://git-lfs.github.com/spec/v1
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oid sha256:01dfbd307d1a37854fa9142596d7529444bdb175fffa01c9e7ca551cefbb2d6d
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size 560
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