---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: student_s3d_default_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_s3d_default_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: 0.3789
- Accuracy: 0.885
- F1: 0.8847
- Precision: 0.8893

## 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: 75
- eval_batch_size: 75
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 47
- training_steps: 475
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.6345        | 2.0147  | 47   | 0.5707          | 0.7656   | 0.7621 | 0.7824    |
| 0.4332        | 4.0295  | 94   | 0.3666          | 0.8219   | 0.8218 | 0.8222    |
| 0.3306        | 7.0021  | 141  | 0.4903          | 0.825    | 0.8246 | 0.8283    |
| 0.2447        | 9.0168  | 188  | 0.3415          | 0.8375   | 0.8361 | 0.8498    |
| 0.1972        | 11.0316 | 235  | 0.4171          | 0.8375   | 0.8359 | 0.8516    |
| 0.173         | 14.0042 | 282  | 0.3911          | 0.8656   | 0.8650 | 0.8720    |
| 0.1481        | 16.0189 | 329  | 0.4326          | 0.8719   | 0.8714 | 0.8772    |
| 0.1165        | 18.0337 | 376  | 0.2364          | 0.8812   | 0.8811 | 0.8834    |
| 0.098         | 21.0063 | 423  | 0.5760          | 0.8844   | 0.8843 | 0.8856    |
| 0.0857        | 23.0211 | 470  | 0.5217          | 0.8812   | 0.8811 | 0.8827    |


### Framework versions

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