videomae-base-groub13-14-finetuned-SLT-subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9463
- Accuracy: 1.0
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 224
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
3.0689 | 0.07 | 15 | 2.9460 | 0.1 |
3.1203 | 1.07 | 30 | 2.7839 | 0.15 |
2.8375 | 2.07 | 45 | 2.6131 | 0.2 |
2.619 | 3.07 | 60 | 2.5076 | 0.2 |
2.455 | 4.07 | 75 | 2.4382 | 0.15 |
2.4831 | 5.07 | 90 | 2.3911 | 0.25 |
2.5183 | 6.07 | 105 | 2.3353 | 0.3 |
2.4267 | 7.07 | 120 | 2.2589 | 0.35 |
2.257 | 8.07 | 135 | 2.1845 | 0.4 |
2.1795 | 9.07 | 150 | 2.0329 | 0.6 |
1.9706 | 10.07 | 165 | 1.7614 | 0.9 |
1.7866 | 11.07 | 180 | 1.4249 | 0.95 |
1.4293 | 12.07 | 195 | 1.1991 | 0.9 |
0.9984 | 13.07 | 210 | 1.0114 | 0.95 |
0.9409 | 14.06 | 224 | 0.9463 | 1.0 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for asmaa1/videomae-base-groub13-14-finetuned-SLT-subset
Base model
MCG-NJU/videomae-base