File size: 2,066 Bytes
fbcf44c c2ff59f fbcf44c c2ff59f fbcf44c c2ff59f a3b909e fbcf44c c2ff59f fbcf44c |
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: working
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. -->
# working
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: 4.6095
- Accuracy: 0.0266
- Top 1 Accuracy: 0.0266
- Top 5 Accuracy: 0.0858
- Top 10 Accuracy: 0.1420
- Macro Precision: 0.0024
- Macro Recall: 0.0173
- Macro F1: 0.0039
- Pearson Corr: 0.3016
- Spearman Corr: 0.2739
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 900
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Top 1 Accuracy | Top 5 Accuracy | Top 10 Accuracy | Macro Precision | Macro Recall | Macro F1 | Pearson Corr | Spearman Corr |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:--------------:|:---------------:|:---------------:|:------------:|:--------:|:------------:|:-------------:|
| 4.523 | 5.0542 | 500 | 4.6095 | 0.0266 | 0.0266 | 0.0858 | 0.1420 | 0.0024 | 0.0173 | 0.0039 | 0.3016 | 0.2739 |
### Framework versions
- Transformers 4.44.0
- Pytorch 1.11.0+cu102
- Datasets 2.21.0
- Tokenizers 0.19.1
|