transformers tensorboard safetensors timesformer generated_from_trainer base_model:facebook/timesformer-base-finetuned-k400 license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: facebook/timesformer-base-finetuned-k400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: timesformer-base-finetuned-k400-finetuned-ucf101-subset
  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. -->

# timesformer-base-finetuned-k400-finetuned-ucf101-subset

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: 1.6472
- Accuracy: 0.5994

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4112        | 0.1   | 300  | 4.3165          | 0.1141   |
| 2.1452        | 1.1   | 600  | 2.0349          | 0.3758   |
| 2.156         | 2.1   | 900  | 1.9146          | 0.2752   |
| 0.7848        | 3.1   | 1200 | 2.9334          | 0.2550   |
| 3.2405        | 4.1   | 1500 | 2.6900          | 0.3557   |
| 2.6131        | 5.1   | 1800 | 2.5973          | 0.3691   |
| 1.5998        | 6.1   | 2100 | 3.1545          | 0.4295   |
| 1.1689        | 7.1   | 2400 | 3.3012          | 0.2953   |
| 0.2398        | 8.1   | 2700 | 2.7231          | 0.4362   |
| 1.2448        | 9.1   | 3000 | 2.6949          | 0.4295   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
