---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: videomae-base-finetuned-cricket_shot_detection_18
  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-cricket_shot_detection_18

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: 1.4708
- Accuracy: 0.5789
- F1: 0.5987
- Recall: 0.5789
- Precision: 0.7316

## 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: 6e-06
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 288

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 1.7521        | 0.1701 | 49   | 1.7640          | 0.1579   | 0.1971 | 0.1579 | 0.2632    |
| 1.6025        | 1.1701 | 98   | 1.6926          | 0.2105   | 0.2205 | 0.2105 | 0.2782    |
| 1.3708        | 2.1701 | 147  | 1.6164          | 0.3158   | 0.3062 | 0.3158 | 0.3544    |
| 1.1786        | 3.1701 | 196  | 1.5217          | 0.4211   | 0.4042 | 0.4211 | 0.4158    |
| 1.0709        | 4.1701 | 245  | 1.4708          | 0.5789   | 0.5987 | 0.5789 | 0.7316    |
| 1.0057        | 5.1493 | 288  | 1.4721          | 0.5789   | 0.5982 | 0.5789 | 0.7246    |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0