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---
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library_name: transformers
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tags:
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- generated_from_trainer
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model-index:
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- name: videomae-diving48-multilabel-finetuned
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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-diving48-multilabel-finetuned
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3969
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- F1 Macro: 0.2636
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- Precision Macro: 0.2180
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- Recall Macro: 0.4145
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- Exact Match Ratio: 0.0003
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- Hamming Accuracy: 0.7557
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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: 0.0002
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 25544
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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 | F1 Macro | Precision Macro | Recall Macro | Exact Match Ratio | Hamming Accuracy |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:-----------------:|:----------------:|
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| 1.3045 | 0.1250 | 3194 | 1.4774 | 0.1609 | 0.1518 | 0.2915 | 0.0 | 0.7280 |
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| 0.8881 | 1.1250 | 6388 | 1.4002 | 0.2035 | 0.1952 | 0.3239 | 0.0 | 0.7537 |
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| 1.0683 | 2.1250 | 9582 | 1.4017 | 0.2014 | 0.1999 | 0.3470 | 0.0 | 0.7403 |
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| 0.7672 | 3.1250 | 12776 | 1.4316 | 0.2280 | 0.1893 | 0.3459 | 0.0022 | 0.7566 |
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| 0.8529 | 4.1250 | 15970 | 1.4307 | 0.2333 | 0.2011 | 0.3484 | 0.0003 | 0.7650 |
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| 1.0022 | 5.1250 | 19164 | 1.4566 | 0.2367 | 0.2095 | 0.3404 | 0.0005 | 0.7734 |
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| 1.3422 | 6.1250 | 22358 | 1.4297 | 0.2602 | 0.2127 | 0.3922 | 0.0005 | 0.7634 |
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| 1.0641 | 7.1247 | 25544 | 1.3969 | 0.2636 | 0.2180 | 0.4145 | 0.0003 | 0.7557 |
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.1.0+cu118
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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