---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-scratch_1
  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-scratch_1

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: 1.6254
- Accuracy: 0.7624

## 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: 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: 30192

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5872        | 0.01  | 420   | 0.6884          | 0.5518   |
| 0.5358        | 1.01  | 840   | 0.6766          | 0.6194   |
| 0.5339        | 2.01  | 1260  | 0.6295          | 0.6430   |
| 0.4483        | 3.01  | 1680  | 0.7323          | 0.5957   |
| 0.4654        | 4.01  | 2100  | 0.7020          | 0.6486   |
| 0.3897        | 5.01  | 2520  | 0.7636          | 0.6498   |
| 0.3386        | 6.01  | 2940  | 0.8877          | 0.6610   |
| 0.3601        | 7.01  | 3360  | 0.8791          | 0.6486   |
| 0.3401        | 8.01  | 3780  | 0.7403          | 0.6633   |
| 0.3113        | 9.01  | 4200  | 0.7316          | 0.6959   |
| 0.2096        | 10.01 | 4620  | 0.9519          | 0.6982   |
| 0.1537        | 11.01 | 5040  | 0.9116          | 0.7016   |
| 0.1113        | 12.01 | 5460  | 1.0047          | 0.6971   |
| 0.3247        | 13.01 | 5880  | 1.2167          | 0.6847   |
| 0.171         | 14.01 | 6300  | 0.9337          | 0.7027   |
| 0.3076        | 15.01 | 6720  | 1.1811          | 0.7207   |
| 0.2927        | 16.01 | 7140  | 1.0953          | 0.7218   |
| 0.1679        | 17.01 | 7560  | 1.2948          | 0.7207   |
| 0.1523        | 18.01 | 7980  | 1.3632          | 0.7016   |
| 0.1059        | 19.01 | 8400  | 1.2915          | 0.7185   |
| 0.1741        | 20.01 | 8820  | 1.2315          | 0.7432   |
| 0.0629        | 21.01 | 9240  | 1.3948          | 0.7230   |
| 0.0075        | 22.01 | 9660  | 1.1435          | 0.7376   |
| 0.1692        | 23.01 | 10080 | 1.3998          | 0.7128   |
| 0.0347        | 24.01 | 10500 | 1.4803          | 0.7027   |
| 0.0396        | 25.01 | 10920 | 1.6457          | 0.7005   |
| 0.0074        | 26.01 | 11340 | 1.5602          | 0.7050   |
| 0.1256        | 27.01 | 11760 | 1.3965          | 0.7173   |
| 0.0021        | 28.01 | 12180 | 1.4514          | 0.7342   |
| 0.0476        | 29.01 | 12600 | 1.2915          | 0.7173   |
| 0.0065        | 30.01 | 13020 | 1.3397          | 0.7095   |
| 0.0435        | 31.01 | 13440 | 1.8912          | 0.6948   |
| 0.0268        | 32.01 | 13860 | 1.5767          | 0.7286   |
| 0.0487        | 33.01 | 14280 | 1.6439          | 0.6948   |
| 0.0448        | 34.01 | 14700 | 1.5990          | 0.7354   |
| 0.0166        | 35.01 | 15120 | 1.3866          | 0.7466   |
| 0.1029        | 36.01 | 15540 | 1.7427          | 0.7106   |
| 0.0678        | 37.01 | 15960 | 1.4194          | 0.7365   |
| 0.0007        | 38.01 | 16380 | 1.9137          | 0.7072   |
| 0.0602        | 39.01 | 16800 | 1.6180          | 0.7309   |
| 0.0977        | 40.01 | 17220 | 1.5710          | 0.7354   |
| 0.0606        | 41.01 | 17640 | 1.3908          | 0.7342   |
| 0.1046        | 42.01 | 18060 | 1.7846          | 0.7252   |
| 0.0004        | 43.01 | 18480 | 1.6396          | 0.7241   |
| 0.0881        | 44.01 | 18900 | 1.6206          | 0.7196   |
| 0.0934        | 45.01 | 19320 | 1.6994          | 0.7320   |
| 0.0001        | 46.01 | 19740 | 2.0068          | 0.7162   |
| 0.024         | 47.01 | 20160 | 1.5350          | 0.7376   |
| 0.017         | 48.01 | 20580 | 1.8864          | 0.7162   |
| 0.121         | 49.01 | 21000 | 1.6862          | 0.7230   |
| 0.0001        | 50.01 | 21420 | 1.8462          | 0.7365   |
| 0.0319        | 51.01 | 21840 | 1.9072          | 0.7286   |
| 0.065         | 52.01 | 22260 | 1.6631          | 0.7556   |
| 0.0424        | 53.01 | 22680 | 1.9177          | 0.7399   |
| 0.0001        | 54.01 | 23100 | 1.8990          | 0.7365   |
| 0.0           | 55.01 | 23520 | 2.0622          | 0.7455   |
| 0.0582        | 56.01 | 23940 | 1.4821          | 0.7444   |
| 0.0001        | 57.01 | 24360 | 1.6254          | 0.7624   |
| 0.0           | 58.01 | 24780 | 1.8024          | 0.7545   |
| 0.0486        | 59.01 | 25200 | 1.6804          | 0.7545   |
| 0.0001        | 60.01 | 25620 | 1.7991          | 0.7523   |
| 0.0           | 61.01 | 26040 | 1.8281          | 0.7511   |
| 0.0022        | 62.01 | 26460 | 1.8172          | 0.75     |
| 0.0001        | 63.01 | 26880 | 1.9532          | 0.7489   |
| 0.0           | 64.01 | 27300 | 1.9209          | 0.7477   |
| 0.0           | 65.01 | 27720 | 1.9100          | 0.7579   |
| 0.0           | 66.01 | 28140 | 1.9572          | 0.7534   |
| 0.0007        | 67.01 | 28560 | 2.0380          | 0.75     |
| 0.0627        | 68.01 | 28980 | 1.8911          | 0.7579   |
| 0.0002        | 69.01 | 29400 | 1.9255          | 0.75     |
| 0.0           | 70.01 | 29820 | 1.9195          | 0.7568   |
| 0.0           | 71.01 | 30192 | 1.9317          | 0.75     |


### Framework versions

- Transformers 4.39.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2