update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,79 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: cc-by-nc-4.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
model-index:
|
| 8 |
+
- name: videomae-base-finetuned-ucf_crime2
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# videomae-base-finetuned-ucf_crime2
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 1.8463
|
| 20 |
+
- Accuracy: 0.5200
|
| 21 |
+
|
| 22 |
+
## Model description
|
| 23 |
+
|
| 24 |
+
More information needed
|
| 25 |
+
|
| 26 |
+
## Intended uses & limitations
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Training and evaluation data
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Training procedure
|
| 35 |
+
|
| 36 |
+
### Training hyperparameters
|
| 37 |
+
|
| 38 |
+
The following hyperparameters were used during training:
|
| 39 |
+
- learning_rate: 5e-05
|
| 40 |
+
- train_batch_size: 2
|
| 41 |
+
- eval_batch_size: 2
|
| 42 |
+
- seed: 42
|
| 43 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 44 |
+
- lr_scheduler_type: linear
|
| 45 |
+
- lr_scheduler_warmup_ratio: 0.1
|
| 46 |
+
- training_steps: 2700
|
| 47 |
+
|
| 48 |
+
### Training results
|
| 49 |
+
|
| 50 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 51 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 52 |
+
| 0.475 | 0.05 | 135 | 0.9935 | 0.6004 |
|
| 53 |
+
| 1.44 | 1.05 | 270 | 1.4196 | 0.4274 |
|
| 54 |
+
| 1.1084 | 2.05 | 405 | 0.9135 | 0.6737 |
|
| 55 |
+
| 0.8732 | 3.05 | 540 | 1.1984 | 0.5479 |
|
| 56 |
+
| 1.4184 | 4.05 | 675 | 1.3373 | 0.4926 |
|
| 57 |
+
| 1.1355 | 5.05 | 810 | 0.9888 | 0.6148 |
|
| 58 |
+
| 0.4522 | 6.05 | 945 | 1.0745 | 0.5694 |
|
| 59 |
+
| 0.7754 | 7.05 | 1080 | 1.5848 | 0.5330 |
|
| 60 |
+
| 1.1235 | 8.05 | 1215 | 1.3688 | 0.5753 |
|
| 61 |
+
| 1.611 | 9.05 | 1350 | 0.6958 | 0.7694 |
|
| 62 |
+
| 0.5714 | 10.05 | 1485 | 0.8027 | 0.7542 |
|
| 63 |
+
| 0.716 | 11.05 | 1620 | 1.3503 | 0.6782 |
|
| 64 |
+
| 0.6642 | 12.05 | 1755 | 1.0798 | 0.6957 |
|
| 65 |
+
| 0.8451 | 13.05 | 1890 | 1.2328 | 0.7479 |
|
| 66 |
+
| 0.6157 | 14.05 | 2025 | 1.9403 | 0.5762 |
|
| 67 |
+
| 0.3358 | 15.05 | 2160 | 1.3435 | 0.6939 |
|
| 68 |
+
| 0.5394 | 16.05 | 2295 | 1.2524 | 0.7056 |
|
| 69 |
+
| 0.3334 | 17.05 | 2430 | 1.1190 | 0.7645 |
|
| 70 |
+
| 0.3513 | 18.05 | 2565 | 1.2137 | 0.7461 |
|
| 71 |
+
| 0.2531 | 19.05 | 2700 | 1.2131 | 0.7362 |
|
| 72 |
+
|
| 73 |
+
|
| 74 |
+
### Framework versions
|
| 75 |
+
|
| 76 |
+
- Transformers 4.29.2
|
| 77 |
+
- Pytorch 1.13.1+cu117
|
| 78 |
+
- Datasets 2.12.0
|
| 79 |
+
- Tokenizers 0.13.3
|