---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: videomae-base-finetuned-kinetics-fight_18-03-2024
  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-kinetics-fight_18-03-2024

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: 0.2211
- Accuracy: 0.9175
- Precision: 0.9372
- Recall: 0.895

## 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-07
- train_batch_size: 12
- eval_batch_size: 12
- 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: 2660

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
| 0.7318        | 0.05  | 134  | 0.7169          | 0.43     | 0.4247    | 0.395  |
| 0.6646        | 1.05  | 268  | 0.6636          | 0.59     | 0.6139    | 0.485  |
| 0.6089        | 2.05  | 402  | 0.5944          | 0.78     | 0.8415    | 0.69   |
| 0.5485        | 3.05  | 536  | 0.5270          | 0.845    | 0.8920    | 0.785  |
| 0.4581        | 4.05  | 670  | 0.4630          | 0.865    | 0.9011    | 0.82   |
| 0.3436        | 5.05  | 804  | 0.3994          | 0.8725   | 0.9162    | 0.82   |
| 0.3109        | 6.05  | 938  | 0.3530          | 0.8775   | 0.9171    | 0.83   |
| 0.2672        | 7.05  | 1072 | 0.3212          | 0.88     | 0.9176    | 0.835  |
| 0.2243        | 8.05  | 1206 | 0.2947          | 0.895    | 0.9202    | 0.865  |
| 0.297         | 9.05  | 1340 | 0.2779          | 0.895    | 0.9202    | 0.865  |
| 0.21          | 10.05 | 1474 | 0.2615          | 0.9025   | 0.9215    | 0.88   |
| 0.2003        | 11.05 | 1608 | 0.2515          | 0.895    | 0.9202    | 0.865  |
| 0.2128        | 12.05 | 1742 | 0.2418          | 0.91     | 0.9271    | 0.89   |
| 0.1789        | 13.05 | 1876 | 0.2357          | 0.9125   | 0.9275    | 0.895  |
| 0.1672        | 14.05 | 2010 | 0.2300          | 0.91     | 0.9227    | 0.895  |
| 0.1532        | 15.05 | 2144 | 0.2275          | 0.9175   | 0.9372    | 0.895  |
| 0.1695        | 16.05 | 2278 | 0.2241          | 0.9125   | 0.9275    | 0.895  |
| 0.1255        | 17.05 | 2412 | 0.2225          | 0.915    | 0.9323    | 0.895  |
| 0.1168        | 18.05 | 2546 | 0.2214          | 0.9175   | 0.9372    | 0.895  |
| 0.1395        | 19.04 | 2660 | 0.2211          | 0.9175   | 0.9372    | 0.895  |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2