transformers safetensors videomae video-classification generated_from_trainer base_model:MCG-NJU/videomae-large license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: videomae-large-fight_22-01-2024
  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. -->

# videomae-large-fight_22-01-2024

This model is a fine-tuned version of [MCG-NJU/videomae-large](https://huggingface.co/MCG-NJU/videomae-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6263
- Accuracy: 0.8565
- Precision: 0.8502
- Recall: 0.8655

## 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: 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: 9080

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
| 0.6582        | 0.05  | 454  | 0.6970          | 0.5695   | 0.5660    | 0.5964 |
| 0.6712        | 1.05  | 908  | 0.6281          | 0.6390   | 0.6202    | 0.7175 |
| 0.5664        | 2.05  | 1362 | 0.6718          | 0.6457   | 0.6555    | 0.6143 |
| 0.5645        | 3.05  | 1816 | 0.5835          | 0.7018   | 0.6974    | 0.7130 |
| 0.4259        | 4.05  | 2270 | 0.5497          | 0.7197   | 0.7402    | 0.6771 |
| 0.3542        | 5.05  | 2724 | 0.5509          | 0.7466   | 0.7434    | 0.7534 |
| 0.3676        | 6.05  | 3178 | 0.4956          | 0.7623   | 0.7532    | 0.7803 |
| 0.2656        | 7.05  | 3632 | 0.5263          | 0.7534   | 0.7811    | 0.7040 |
| 0.4675        | 8.05  | 4086 | 0.5216          | 0.7915   | 0.8009    | 0.7758 |
| 0.1434        | 9.05  | 4540 | 0.4744          | 0.8094   | 0.8136    | 0.8027 |
| 0.1389        | 10.05 | 4994 | 0.5389          | 0.8318   | 0.8274    | 0.8386 |
| 0.3228        | 11.05 | 5448 | 0.5345          | 0.8341   | 0.8599    | 0.7982 |
| 0.1044        | 12.05 | 5902 | 0.5729          | 0.8341   | 0.8465    | 0.8161 |
| 0.0305        | 13.05 | 6356 | 0.5812          | 0.8363   | 0.8378    | 0.8341 |
| 0.1256        | 14.05 | 6810 | 0.5806          | 0.8520   | 0.8489    | 0.8565 |
| 0.2735        | 15.05 | 7264 | 0.5713          | 0.8520   | 0.8618    | 0.8386 |
| 0.2376        | 16.05 | 7718 | 0.6030          | 0.8498   | 0.8578    | 0.8386 |
| 0.2978        | 17.05 | 8172 | 0.6263          | 0.8565   | 0.8502    | 0.8655 |
| 0.3872        | 18.05 | 8626 | 0.6099          | 0.8520   | 0.8489    | 0.8565 |
| 0.6629        | 19.05 | 9080 | 0.6142          | 0.8543   | 0.8496    | 0.8610 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
