---
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_12_latest
  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_12_latest

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: 1.4676
- Accuracy: 0.6316
- F1: 0.6366
- Recall: 0.6316
- Precision: 0.7675

## 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: 8
- eval_batch_size: 8
- 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: 576

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 1.7629        | 0.1267 | 73   | 1.8203          | 0.2105   | 0.1815 | 0.2105 | 0.1974    |
| 1.5269        | 1.1267 | 146  | 1.7099          | 0.2632   | 0.2731 | 0.2632 | 0.5474    |
| 1.2084        | 2.1267 | 219  | 1.5873          | 0.5789   | 0.5797 | 0.5789 | 0.7570    |
| 1.1034        | 3.1267 | 292  | 1.5001          | 0.5789   | 0.5797 | 0.5789 | 0.7570    |
| 0.9862        | 4.1267 | 365  | 1.4676          | 0.6316   | 0.6366 | 0.6316 | 0.7675    |
| 0.891         | 5.1267 | 438  | 1.4256          | 0.6316   | 0.6366 | 0.6316 | 0.7675    |
| 0.6645        | 6.1267 | 511  | 1.4055          | 0.6316   | 0.6476 | 0.6316 | 0.8184    |
| 0.7161        | 7.1128 | 576  | 1.4041          | 0.6316   | 0.6366 | 0.6316 | 0.7675    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.19.1