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: 0.5324
- Accuracy: 0.7871
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 |
---|---|---|---|---|
2.3271 | 0.13 | 19 | 2.1350 | 0.2429 |
1.9566 | 1.13 | 38 | 1.4260 | 0.5857 |
1.0941 | 2.13 | 57 | 0.8857 | 0.7143 |
0.5363 | 3.13 | 76 | 0.6664 | 0.7143 |
0.3392 | 4.13 | 95 | 0.4023 | 0.9143 |
0.1765 | 5.13 | 114 | 0.3487 | 0.9 |
0.1318 | 6.13 | 133 | 0.3181 | 0.9 |
0.1092 | 7.1 | 148 | 0.2886 | 0.9 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
- 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 smc/videomae-base-finetuned-ucf101-subset
Base model
MCG-NJU/videomae-base