README.md

---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# videomae-base-finetuned-numbers-augmented2

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: 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