---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mdeberta-v3-base-azsci-topics
  results: []
datasets:
- hajili/azsci_topics
language:
- az
---

<!-- 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. -->

# mdeberta-v3-base-azsci-topics

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on [hajili/azsci_topics](https://huggingface.co/datasets/hajili/azsci_topics) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5213
- Precision: 0.8633
- Recall: 0.8759
- F1: 0.8685
- Accuracy: 0.8759

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 288  | 0.9919          | 0.6713    | 0.7465 | 0.6959 | 0.7465   |
| 1.4813        | 2.0   | 576  | 0.7035          | 0.7994    | 0.8238 | 0.8022 | 0.8238   |
| 1.4813        | 3.0   | 864  | 0.5605          | 0.8540    | 0.8568 | 0.8462 | 0.8568   |
| 0.5512        | 4.0   | 1152 | 0.5296          | 0.8615    | 0.8689 | 0.8623 | 0.8689   |
| 0.5512        | 5.0   | 1440 | 0.5213          | 0.8633    | 0.8759 | 0.8685 | 0.8759   |


### Evaluation results

| Topic              |   Precision |   Recall |       F1 |   Support |
|:-------------------|------------:|---------:|---------:|----------:|
| Aqrar elmlər       |    0.678571 | 0.703704 | 0.690909 |        27 |
| Astronomiya        |    0        | 0        | 0        |         2 |
| Biologiya elmləri  |    0.877358 | 0.885714 | 0.881517 |       105 |
| Coğrafiya          |    0.833333 | 0.882353 | 0.857143 |        17 |
| Filologiya elmləri |    0.932203 | 0.942857 | 0.9375   |       175 |
| Fizika             |    0.763158 | 0.852941 | 0.805556 |        34 |
| Fəlsəfə            |    0.294118 | 0.357143 | 0.322581 |        14 |
| Hüquq elmləri      |    0.965517 | 0.965517 | 0.965517 |        29 |
| Kimya              |    0.828571 | 0.95082  | 0.885496 |        61 |
| Memarlıq           |    0        | 0        | 0        |         5 |
| Mexanika           |    0        | 0        | 0        |         4 |
| Pedaqogika         |    0.882353 | 0.957447 | 0.918367 |        47 |
| Psixologiya        |    1        | 0.722222 | 0.83871  |        18 |
| Riyaziyyat         |    0.871795 | 0.871795 | 0.871795 |        39 |
| Siyasi elmlər      |    0.807692 | 0.84     | 0.823529 |        25 |
| Sosiologiya        |    0        | 0        | 0        |         4 |
| Sənətşünaslıq      |    0.82     | 0.87234  | 0.845361 |        47 |
| Tarix              |    0.846154 | 0.846154 | 0.846154 |        78 |
| Texnika elmləri    |    0.822917 | 0.759615 | 0.79     |       104 |
| Tibb elmləri       |    0.953947 | 0.97973  | 0.966667 |       148 |
| Yer elmləri        |    0.7      | 0.538462 | 0.608696 |        13 |
| İqtisad elmləri    |    0.948052 | 0.960526 | 0.954248 |       152 |
| Əczaçılıq elmləri  |    0        | 0        | 0        |         4 |
| macro avg          |    0.644597 | 0.647363 | 0.643902 |      1152 |
| weighted avg       |    0.863306 | 0.875868 | 0.868519 |      1152 |

### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2