---
library_name: transformers
license: mit
base_model: mateiaassAI/teacher_ag-news
tags:
- generated_from_trainer
datasets:
- moroco
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: teacher_agnews_moroco-demo
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: moroco
      type: moroco
      config: moroco
      split: validation
      args: moroco
    metrics:
    - name: F1
      type: f1
      value: 0.8679107737455669
    - name: Accuracy
      type: accuracy
      value: 0.8549231548724877
    - name: Precision
      type: precision
      value: 0.8702091440403067
    - name: Recall
      type: recall
      value: 0.8671379372847562
---

<!-- 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. -->

# teacher_agnews_moroco-demo

This model is a fine-tuned version of [mateiaassAI/teacher_ag-news](https://huggingface.co/mateiaassAI/teacher_ag-news) on the moroco dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0995
- F1: 0.8679
- Roc Auc: None
- Accuracy: 0.8549
- Precision: 0.8702
- Recall: 0.8671

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:---------:|:------:|
| 0.1183        | 1.0   | 1358 | 0.1007          | 0.8613 | None    | 0.8500   | 0.8751    | 0.8528 |
| 0.0811        | 2.0   | 2716 | 0.0991          | 0.8688 | None    | 0.8546   | 0.8791    | 0.8590 |
| 0.0567        | 3.0   | 4074 | 0.0995          | 0.8679 | None    | 0.8549   | 0.8702    | 0.8671 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0