---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-lift-data-resize
  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-lift-data-resize

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: 0.8146
- Accuracy: 0.7681

## 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: 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: 156

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.5758        | 0.1282 | 20   | 1.6619          | 0.2901   |
| 1.3067        | 1.1282 | 40   | 1.6048          | 0.2990   |
| 1.3787        | 2.1282 | 60   | 1.4723          | 0.3181   |
| 1.1642        | 3.1282 | 80   | 1.4191          | 0.3004   |
| 1.1172        | 4.1282 | 100  | 1.2374          | 0.3196   |
| 0.8982        | 5.1282 | 120  | 1.0099          | 0.5655   |
| 0.915         | 6.1282 | 140  | 0.9540          | 0.5891   |
| 0.7809        | 7.1026 | 156  | 0.9189          | 0.5714   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.0.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1