videomae-base-finetuned-ucf101-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: 0.2267
- Accuracy: 0.9290
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: 16
- eval_batch_size: 16
- 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: 148
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.0466 | 0.1284 | 19 | 1.6349 | 0.6143 |
1.348 | 1.1284 | 38 | 0.8041 | 0.8429 |
0.6208 | 2.1284 | 57 | 0.7583 | 0.7286 |
0.332 | 3.1284 | 76 | 0.4557 | 0.8286 |
0.2229 | 4.1284 | 95 | 0.3133 | 0.8857 |
0.1479 | 5.1284 | 114 | 0.2872 | 0.9 |
0.0761 | 6.1284 | 133 | 0.2888 | 0.9 |
0.0696 | 7.1014 | 148 | 0.2664 | 0.9143 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.1.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1
- Downloads last month
- 4
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for PergaZuZ/videomae-base-finetuned-ucf101-subset
Base model
MCG-NJU/videomae-base