File size: 2,122 Bytes
0659a78 f26b943 0659a78 |
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 73 |
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-scratch
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-scratch
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9263
- Accuracy: 0.7994
## 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: 12
- eval_batch_size: 12
- 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: 3952
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6869 | 0.08 | 330 | 0.6326 | 0.6490 |
| 0.6342 | 1.08 | 660 | 0.6356 | 0.6447 |
| 0.6718 | 2.08 | 990 | 0.6112 | 0.6648 |
| 0.5003 | 3.08 | 1320 | 0.5741 | 0.6991 |
| 0.4131 | 4.08 | 1650 | 0.5480 | 0.7077 |
| 0.3233 | 5.08 | 1980 | 0.5564 | 0.7464 |
| 0.2411 | 6.08 | 2310 | 0.4929 | 0.7923 |
| 0.3402 | 7.08 | 2640 | 0.7592 | 0.7593 |
| 0.2174 | 8.08 | 2970 | 0.7752 | 0.7779 |
| 0.1706 | 9.08 | 3300 | 0.8511 | 0.7923 |
| 0.1127 | 10.08 | 3630 | 0.9263 | 0.7994 |
| 0.062 | 11.08 | 3952 | 1.0187 | 0.7808 |
### Framework versions
- Transformers 4.39.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|