---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: student_videomobilevit_not_learning_RWF2000
  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. -->

# student_videomobilevit_not_learning_RWF2000

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6661
- Accuracy: 0.77
- F1: 0.7689
- Precision: 0.7750

## 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: 1e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 180
- training_steps: 1800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.5117        | 2.02  | 180  | 0.4612          | 0.7844   | 0.7841 | 0.7857    |
| 0.3803        | 4.04  | 360  | 0.4049          | 0.8156   | 0.8150 | 0.8201    |
| 0.3181        | 7.02  | 540  | 0.4287          | 0.8      | 0.7989 | 0.8069    |
| 0.2548        | 9.04  | 720  | 0.4230          | 0.8094   | 0.8080 | 0.8184    |
| 0.2348        | 12.02 | 900  | 0.3655          | 0.85     | 0.85   | 0.85      |
| 0.1722        | 14.04 | 1080 | 0.3827          | 0.8594   | 0.8594 | 0.8595    |
| 0.1861        | 17.02 | 1260 | 0.4371          | 0.8562   | 0.8562 | 0.8571    |
| 0.1753        | 19.04 | 1440 | 0.4214          | 0.8438   | 0.8435 | 0.8457    |
| 0.1464        | 22.02 | 1620 | 0.5414          | 0.8438   | 0.8427 | 0.8531    |
| 0.1411        | 24.04 | 1800 | 0.4668          | 0.8531   | 0.8530 | 0.8542    |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.0.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.0