metadata
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: videomae-diving48-multilabel-finetuned
results: []
videomae-diving48-multilabel-finetuned
This model is a fine-tuned version of 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