---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Matcha_clips_224_fintuned_4
  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. -->

# Matcha_clips_224_fintuned_4

This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3148
- Accuracy: 0.6951

## 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
- optimizer: Use OptimizerNames.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: 1150

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7589        | 0.1   | 115  | 1.4438          | 0.5244   |
| 0.8991        | 1.1   | 230  | 1.0762          | 0.6220   |
| 0.2382        | 2.1   | 345  | 0.9143          | 0.6951   |
| 0.1739        | 3.1   | 460  | 1.1205          | 0.6585   |
| 0.0291        | 4.1   | 575  | 1.1838          | 0.7195   |
| 0.0048        | 5.1   | 690  | 1.1936          | 0.7073   |
| 0.0009        | 6.1   | 805  | 1.2866          | 0.6951   |
| 0.0007        | 7.1   | 920  | 1.3004          | 0.6951   |
| 0.0007        | 8.1   | 1035 | 1.3122          | 0.6951   |
| 0.0006        | 9.1   | 1150 | 1.3148          | 0.6951   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.3.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.1