metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-subset
results: []
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: 0.1371
- Accuracy: 0.9857
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: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- optimizer: Use OptimizerNames.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: 750
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1307 | 0.0333 | 25 | 1.9306 | 0.4286 |
| 1.1542 | 1.0333 | 50 | 1.0325 | 0.6571 |
| 0.8002 | 2.0333 | 75 | 0.8868 | 0.6857 |
| 0.4932 | 3.0333 | 100 | 0.7911 | 0.6857 |
| 0.3413 | 4.0333 | 125 | 0.4311 | 0.8571 |
| 0.111 | 5.0333 | 150 | 0.3425 | 0.8857 |
| 0.1577 | 6.0333 | 175 | 0.2600 | 0.9286 |
| 0.0623 | 7.0333 | 200 | 0.2549 | 0.9286 |
| 0.1271 | 8.0333 | 225 | 0.1371 | 0.9857 |
| 0.0697 | 9.0333 | 250 | 0.1045 | 0.9857 |
| 0.0126 | 10.0333 | 275 | 0.1121 | 0.9857 |
| 0.01 | 11.0333 | 300 | 0.1025 | 0.9857 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0