File size: 2,175 Bytes
d30541f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-kinetics-finetuned-data-no-yolo-colab
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-base-finetuned-kinetics-finetuned-data-no-yolo-colab
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: 0.3187
- Accuracy: 0.9237
## 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: 9e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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: 2057
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5766 | 0.09 | 188 | 0.7504 | 0.7956 |
| 0.4124 | 1.09 | 376 | 0.4797 | 0.8638 |
| 0.104 | 2.09 | 564 | 0.5037 | 0.8583 |
| 0.0652 | 3.09 | 752 | 0.5683 | 0.8556 |
| 0.0821 | 4.09 | 940 | 0.4314 | 0.8992 |
| 0.0015 | 5.09 | 1128 | 0.5824 | 0.8883 |
| 0.0024 | 6.09 | 1316 | 0.4310 | 0.8883 |
| 0.0007 | 7.09 | 1504 | 0.4375 | 0.8992 |
| 0.0007 | 8.09 | 1692 | 0.3199 | 0.9183 |
| 0.0006 | 9.09 | 1880 | 0.3189 | 0.9210 |
| 0.0006 | 10.09 | 2057 | 0.3187 | 0.9237 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|