---
license: cc-by-nc-4.0
base_model: namnh2002/model_timesformer_subset_02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: model_timesformer_subset_02
  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. -->

# model_timesformer_subset_02

This model is a fine-tuned version of [namnh2002/model_timesformer_subset_02](https://huggingface.co/namnh2002/model_timesformer_subset_02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4130
- Accuracy: 0.8852

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 6250

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9368        | 0.1   | 625  | 1.8302          | 0.5026   |
| 0.9936        | 1.1   | 1250 | 1.3368          | 0.6081   |
| 0.9407        | 2.1   | 1875 | 1.1348          | 0.6794   |
| 0.8338        | 3.1   | 2500 | 0.9604          | 0.7270   |
| 0.629         | 4.1   | 3125 | 0.7775          | 0.7684   |
| 0.4094        | 5.1   | 3750 | 0.6939          | 0.8056   |
| 0.398         | 6.1   | 4375 | 0.5883          | 0.8366   |
| 0.3242        | 7.1   | 5000 | 0.4594          | 0.8707   |
| 0.2768        | 8.1   | 5625 | 0.5158          | 0.8604   |
| 0.2571        | 9.1   | 6250 | 0.4130          | 0.8852   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2