---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: videomae-diving48-multilabel-finetuned
  results: []
---

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# videomae-diving48-multilabel-finetuned

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3969
- F1 Macro: 0.2636
- Precision Macro: 0.2180
- Recall Macro: 0.4145
- Exact Match Ratio: 0.0003
- Hamming Accuracy: 0.7557

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 25544
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | F1 Macro | Precision Macro | Recall Macro | Exact Match Ratio | Hamming Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:-----------------:|:----------------:|
| 1.3045        | 0.1250 | 3194  | 1.4774          | 0.1609   | 0.1518          | 0.2915       | 0.0               | 0.7280           |
| 0.8881        | 1.1250 | 6388  | 1.4002          | 0.2035   | 0.1952          | 0.3239       | 0.0               | 0.7537           |
| 1.0683        | 2.1250 | 9582  | 1.4017          | 0.2014   | 0.1999          | 0.3470       | 0.0               | 0.7403           |
| 0.7672        | 3.1250 | 12776 | 1.4316          | 0.2280   | 0.1893          | 0.3459       | 0.0022            | 0.7566           |
| 0.8529        | 4.1250 | 15970 | 1.4307          | 0.2333   | 0.2011          | 0.3484       | 0.0003            | 0.7650           |
| 1.0022        | 5.1250 | 19164 | 1.4566          | 0.2367   | 0.2095          | 0.3404       | 0.0005            | 0.7734           |
| 1.3422        | 6.1250 | 22358 | 1.4297          | 0.2602   | 0.2127          | 0.3922       | 0.0005            | 0.7634           |
| 1.0641        | 7.1247 | 25544 | 1.3969          | 0.2636   | 0.2180          | 0.4145       | 0.0003            | 0.7557           |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.1.0+cu118
- Datasets 3.6.0
- Tokenizers 0.21.1