---
license: cc-by-nc-4.0
base_model: facebook/timesformer-base-finetuned-k600
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 [facebook/timesformer-base-finetuned-k600](https://huggingface.co/facebook/timesformer-base-finetuned-k600) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7125
- Accuracy: 0.5446

## 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: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2997

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8295        | 0.08  | 250  | 1.9005          | 0.4684   |
| 1.6577        | 1.08  | 500  | 1.7229          | 0.4908   |
| 1.4384        | 2.08  | 750  | 1.6627          | 0.5172   |
| 1.2867        | 3.08  | 1000 | 1.7071          | 0.5182   |
| 1.0143        | 4.08  | 1250 | 1.6543          | 0.5381   |
| 0.8775        | 5.08  | 1500 | 1.6755          | 0.5286   |
| 0.9622        | 6.08  | 1750 | 1.6568          | 0.5401   |
| 0.5627        | 7.08  | 2000 | 1.6966          | 0.5371   |
| 0.6586        | 8.08  | 2250 | 1.6735          | 0.5531   |
| 0.4577        | 9.08  | 2500 | 1.7446          | 0.5267   |
| 0.4552        | 10.08 | 2750 | 1.7490          | 0.5371   |
| 0.4488        | 11.08 | 2997 | 1.7125          | 0.5446   |


### Framework versions

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