---
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-check10
  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-check10

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: 0.8682
- Accuracy: 0.6343

## 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: 1e-05
- 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: 2220

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5175        | 0.03  | 56   | 1.6041          | 0.2074   |
| 1.4397        | 1.03  | 112  | 1.4559          | 0.3871   |
| 1.464         | 2.03  | 168  | 1.3637          | 0.3963   |
| 1.3404        | 3.03  | 224  | 1.2467          | 0.4470   |
| 1.3284        | 4.03  | 280  | 1.3115          | 0.3318   |
| 1.1598        | 5.03  | 336  | 1.2489          | 0.4470   |
| 0.9615        | 6.03  | 392  | 1.3057          | 0.4009   |
| 0.9357        | 7.03  | 448  | 0.9201          | 0.6498   |
| 0.9785        | 8.03  | 504  | 0.8629          | 0.6774   |
| 1.0862        | 9.03  | 560  | 1.0977          | 0.5069   |
| 0.9315        | 10.03 | 616  | 0.7868          | 0.7097   |
| 0.9404        | 11.03 | 672  | 0.8170          | 0.6728   |
| 0.939         | 12.03 | 728  | 0.9246          | 0.6636   |
| 0.8205        | 13.03 | 784  | 0.8420          | 0.6866   |
| 0.6719        | 14.03 | 840  | 1.0725          | 0.5899   |
| 0.8308        | 15.03 | 896  | 0.8683          | 0.6912   |
| 0.7554        | 16.03 | 952  | 0.9684          | 0.5991   |
| 0.6962        | 17.03 | 1008 | 1.1106          | 0.5484   |
| 0.7995        | 18.03 | 1064 | 0.9751          | 0.6498   |
| 0.8298        | 19.03 | 1120 | 1.0631          | 0.5300   |
| 0.6607        | 20.03 | 1176 | 0.9458          | 0.6175   |
| 0.688         | 21.03 | 1232 | 1.0296          | 0.6037   |
| 0.5835        | 22.03 | 1288 | 0.8948          | 0.6774   |
| 0.6987        | 23.03 | 1344 | 0.7883          | 0.7189   |
| 0.4979        | 24.03 | 1400 | 0.7089          | 0.7189   |
| 0.6163        | 25.03 | 1456 | 0.7634          | 0.7235   |
| 0.6754        | 26.03 | 1512 | 0.9444          | 0.6359   |
| 0.6673        | 27.03 | 1568 | 0.8391          | 0.6544   |
| 0.4924        | 28.03 | 1624 | 0.8289          | 0.6682   |
| 0.6438        | 29.03 | 1680 | 0.9605          | 0.6129   |
| 0.5714        | 30.03 | 1736 | 0.8838          | 0.6452   |
| 0.6726        | 31.03 | 1792 | 0.8412          | 0.6590   |
| 0.5027        | 32.03 | 1848 | 0.8439          | 0.6728   |
| 0.4649        | 33.03 | 1904 | 0.9525          | 0.6267   |
| 0.6625        | 34.03 | 1960 | 0.7850          | 0.7281   |
| 0.5793        | 35.03 | 2016 | 0.8481          | 0.6728   |
| 0.6411        | 36.03 | 2072 | 0.8842          | 0.6590   |
| 0.6592        | 37.03 | 2128 | 0.8028          | 0.6912   |
| 0.5524        | 38.03 | 2184 | 0.8216          | 0.6866   |
| 0.5697        | 39.02 | 2220 | 0.8339          | 0.6774   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0