---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/timesformer-base-finetuned-k400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-timesformer-d1
  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. -->

# vivit-timesformer-d1

This model is a fine-tuned version of [facebook/timesformer-base-finetuned-k400](https://huggingface.co/facebook/timesformer-base-finetuned-k400) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4413
- Accuracy: 0.7876

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 12010
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4177        | 0.1   | 1201  | 1.6974          | 0.6286   |
| 1.3055        | 1.1   | 2402  | 1.7565          | 0.6570   |
| 0.8467        | 2.1   | 3603  | 1.7238          | 0.6763   |
| 0.0019        | 3.1   | 4804  | 1.6070          | 0.6877   |
| 1.0625        | 4.1   | 6005  | 1.6971          | 0.6939   |
| 0.0012        | 5.1   | 7206  | 1.8048          | 0.7005   |
| 0.8867        | 6.1   | 8407  | 1.6243          | 0.7337   |
| 1.7533        | 7.1   | 9608  | 1.3174          | 0.7661   |
| 0.8878        | 8.1   | 10809 | 1.5021          | 0.7828   |
| 0.0005        | 9.1   | 12010 | 1.4413          | 0.7876   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3