---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-subset
  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-base-finetuned-subset

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: 1.0747
- Accuracy: 0.6991

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 7020

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9225        | 0.02  | 118  | 0.7363          | 0.7419   |
| 0.8357        | 1.02  | 236  | 0.9119          | 0.7005   |
| 0.474         | 2.02  | 354  | 0.9698          | 0.6820   |
| 0.7899        | 3.02  | 472  | 1.1351          | 0.6774   |
| 0.9015        | 4.02  | 590  | 1.3823          | 0.4977   |
| 0.7402        | 5.02  | 708  | 0.8661          | 0.6959   |
| 0.6343        | 6.02  | 826  | 0.6689          | 0.7005   |
| 0.7427        | 7.02  | 944  | 0.9109          | 0.6728   |
| 0.5898        | 8.02  | 1062 | 1.0127          | 0.5945   |
| 0.6258        | 9.02  | 1180 | 0.7131          | 0.7235   |
| 0.9957        | 10.02 | 1298 | 0.9507          | 0.6728   |
| 0.401         | 11.02 | 1416 | 0.6259          | 0.7189   |
| 0.5422        | 12.02 | 1534 | 0.9453          | 0.6774   |
| 0.6852        | 13.02 | 1652 | 0.8649          | 0.7005   |
| 0.8469        | 14.02 | 1770 | 0.9379          | 0.6912   |
| 0.8492        | 15.02 | 1888 | 0.9003          | 0.6452   |
| 0.7633        | 16.02 | 2006 | 0.7601          | 0.7235   |
| 0.6063        | 17.02 | 2124 | 0.6181          | 0.7788   |
| 0.6436        | 18.02 | 2242 | 0.9445          | 0.6313   |
| 0.8931        | 19.02 | 2360 | 0.8515          | 0.7281   |
| 0.8599        | 20.02 | 2478 | 1.0786          | 0.6359   |
| 0.5183        | 21.02 | 2596 | 0.9481          | 0.6866   |
| 0.7982        | 22.02 | 2714 | 0.8364          | 0.7235   |
| 1.0003        | 23.02 | 2832 | 0.7811          | 0.7327   |
| 0.6666        | 24.02 | 2950 | 0.7552          | 0.7465   |
| 0.8527        | 25.02 | 3068 | 0.8201          | 0.7189   |
| 0.4678        | 26.02 | 3186 | 1.0260          | 0.6959   |
| 0.7354        | 27.02 | 3304 | 0.8520          | 0.6866   |
| 1.1097        | 28.02 | 3422 | 0.9239          | 0.7327   |
| 0.6264        | 29.02 | 3540 | 0.6894          | 0.7558   |
| 0.3348        | 30.02 | 3658 | 0.6230          | 0.8065   |
| 0.5548        | 31.02 | 3776 | 0.6431          | 0.8203   |
| 0.4242        | 32.02 | 3894 | 0.8081          | 0.7051   |
| 0.5805        | 33.02 | 4012 | 0.5598          | 0.8203   |
| 0.7064        | 34.02 | 4130 | 0.7341          | 0.7926   |
| 0.2534        | 35.02 | 4248 | 0.6685          | 0.7834   |
| 0.7578        | 36.02 | 4366 | 0.7592          | 0.7604   |
| 0.5822        | 37.02 | 4484 | 0.9472          | 0.7281   |
| 0.2939        | 38.02 | 4602 | 0.8888          | 0.7281   |
| 0.4795        | 39.02 | 4720 | 1.0768          | 0.6636   |
| 0.4038        | 40.02 | 4838 | 0.6452          | 0.8065   |
| 0.8347        | 41.02 | 4956 | 0.7040          | 0.7926   |
| 0.4113        | 42.02 | 5074 | 0.8012          | 0.7373   |
| 0.3681        | 43.02 | 5192 | 0.7622          | 0.7880   |
| 1.0092        | 44.02 | 5310 | 0.7932          | 0.7880   |
| 0.321         | 45.02 | 5428 | 0.9069          | 0.7373   |
| 0.399         | 46.02 | 5546 | 0.6439          | 0.8111   |
| 0.3699        | 47.02 | 5664 | 0.7740          | 0.7696   |
| 0.4297        | 48.02 | 5782 | 0.6811          | 0.8249   |
| 0.2783        | 49.02 | 5900 | 0.5868          | 0.8525   |
| 0.4946        | 50.02 | 6018 | 0.6732          | 0.7926   |
| 0.3058        | 51.02 | 6136 | 0.5511          | 0.8341   |
| 0.1286        | 52.02 | 6254 | 0.5877          | 0.8295   |
| 0.2013        | 53.02 | 6372 | 0.6508          | 0.8157   |
| 0.2027        | 54.02 | 6490 | 0.6630          | 0.8157   |
| 0.6267        | 55.02 | 6608 | 0.7373          | 0.8065   |
| 0.4561        | 56.02 | 6726 | 0.7383          | 0.8018   |
| 0.7002        | 57.02 | 6844 | 0.7073          | 0.8111   |
| 0.1823        | 58.02 | 6962 | 0.6871          | 0.8203   |
| 0.2439        | 59.01 | 7020 | 0.6901          | 0.8203   |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.13.1
- Datasets 2.16.1
- Tokenizers 0.15.0