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: 0.3402
- Accuracy: 0.9054
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: 8
- eval_batch_size: 8
- 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: 3530
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2221 | 0.0989 | 349 | 1.0476 | 0.6204 |
| 0.7062 | 1.0989 | 698 | 0.7049 | 0.7679 |
| 0.626 | 2.0989 | 1047 | 0.4938 | 0.8394 |
| 0.4414 | 3.0989 | 1396 | 0.5213 | 0.8365 |
| 0.4938 | 4.0989 | 1745 | 0.5057 | 0.8248 |
| 0.4516 | 5.0989 | 2094 | 0.4209 | 0.8730 |
| 0.2555 | 6.0989 | 2443 | 0.4210 | 0.8701 |
| 0.3595 | 7.0989 | 2792 | 0.3525 | 0.8993 |
| 0.2301 | 8.0989 | 3141 | 0.3473 | 0.9036 |
| 0.1837 | 9.0989 | 3490 | 0.3532 | 0.8949 |
| 0.3946 | 10.0113 | 3530 | 0.3517 | 0.8964 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.0.1+cu117
- Datasets 2.21.0
- Tokenizers 0.19.1