---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: videomae-base-finetuned-04-21-finetuned-05-26-finetuned-06-12
  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-04-21-finetuned-05-26-finetuned-06-12

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7016
- Accuracy: 0.5230
- Precision: 0.2735
- Recall: 0.5230
- F1: 0.3592

## 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: Use OptimizerNames.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: 384

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.7187        | 0.2526 | 97   | 0.6909          | 0.5467   | 0.6617    | 0.5467 | 0.4002 |
| 0.6796        | 1.2526 | 194  | 0.6890          | 0.5382   | 0.5214    | 0.5382 | 0.4089 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1