metadata
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: videomae-base-finetuned-numbers-augmented2
results: []
videomae-base-finetuned-numbers-augmented2
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9722
- Accuracy: 0.3269
- F1: 0.2716
- Precision: 0.3970
- Recall: 0.3277
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-06
- 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: 2816
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 2.2279 | 0.2504 | 705 | 2.2645 | 0.1824 | 0.1262 | 0.2559 | 0.1792 |
| 1.7024 | 1.25 | 1409 | 2.0462 | 0.3167 | 0.2828 | 0.3354 | 0.3152 |
| 1.3164 | 2.25 | 2113 | 1.9759 | 0.3081 | 0.2568 | 0.3022 | 0.3085 |
| 1.3877 | 3.2496 | 2816 | 1.9641 | 0.3373 | 0.2839 | 0.3031 | 0.3367 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1