|
---
|
|
license: cc-by-nc-4.0
|
|
base_model: MCG-NJU/videomae-base-finetuned-kinetics
|
|
tags:
|
|
- generated_from_trainer
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: videomae-finetuned_41
|
|
results: []
|
|
---
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
should probably proofread and complete it, then remove this comment. -->
|
|
|
|
# videomae-finetuned_41
|
|
|
|
This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 7.9297
|
|
- Accuracy: 0.3317
|
|
|
|
## 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: 2
|
|
- eval_batch_size: 2
|
|
- seed: 42
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
|
- lr_scheduler_type: linear
|
|
- lr_scheduler_warmup_ratio: 0.2
|
|
- training_steps: 61640
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
|
| 0.5175 | 0.05 | 3083 | 4.6977 | 0.3008 |
|
|
| 0.5311 | 1.05 | 6166 | 5.6012 | 0.3081 |
|
|
| 0.5884 | 2.05 | 9249 | 6.2252 | 0.3175 |
|
|
| 0.5206 | 3.05 | 12332 | 6.7917 | 0.3248 |
|
|
| 0.4449 | 4.05 | 15415 | 6.1943 | 0.3008 |
|
|
| 0.3783 | 5.05 | 18498 | 6.8339 | 0.3150 |
|
|
| 0.5032 | 6.05 | 21581 | 6.6566 | 0.3077 |
|
|
| 0.4091 | 7.05 | 24664 | 6.8013 | 0.2972 |
|
|
| 0.4436 | 8.05 | 27747 | 6.8549 | 0.3 |
|
|
| 0.3474 | 9.05 | 30830 | 7.0015 | 0.3268 |
|
|
| 0.2151 | 10.05 | 33913 | 7.7671 | 0.3041 |
|
|
| 0.3597 | 11.05 | 36996 | 7.0724 | 0.3293 |
|
|
| 0.1673 | 12.05 | 40079 | 7.5805 | 0.3248 |
|
|
| 0.114 | 13.05 | 43162 | 7.8196 | 0.3175 |
|
|
| 0.2088 | 14.05 | 46245 | 7.7103 | 0.3272 |
|
|
| 0.1662 | 15.05 | 49328 | 7.7613 | 0.3248 |
|
|
| 0.1961 | 16.05 | 52411 | 7.7730 | 0.3297 |
|
|
| 0.1436 | 17.05 | 55494 | 7.9297 | 0.3317 |
|
|
| 0.1134 | 18.05 | 58577 | 8.0447 | 0.3268 |
|
|
| 0.0634 | 19.05 | 61640 | 7.9717 | 0.3305 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.38.1
|
|
- Pytorch 2.0.1+cu118
|
|
- Datasets 2.18.0
|
|
- Tokenizers 0.15.2
|
|
|
