---
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-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. -->

# xlm-roberta-large-azsci-topics

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on [azsci_topics](https://huggingface.co/datasets/hajili/azsci_topics) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4012
- Precision: 0.9115
- Recall: 0.9158
- F1: 0.9121
- Accuracy: 0.9158

## 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  | 0.6402          | 0.8063    | 0.8073 | 0.7900 | 0.8073   |
| 1.0792        | 2.0   | 576  | 0.4482          | 0.8827    | 0.8776 | 0.8743 | 0.8776   |
| 1.0792        | 3.0   | 864  | 0.3947          | 0.8968    | 0.9019 | 0.8977 | 0.9019   |
| 0.3135        | 4.0   | 1152 | 0.4177          | 0.9043    | 0.9080 | 0.9047 | 0.9080   |
| 0.3135        | 5.0   | 1440 | 0.4012          | 0.9115    | 0.9158 | 0.9121 | 0.9158   |

### Evaluation results

| Topic              |   Precision |   Recall |       F1 |   Support |
|:-------------------|------------:|---------:|---------:|----------:|
| Aqrar elmlər       |    0.846154 | 0.814815 | 0.830189 |        27 |
| Astronomiya        |    0.666667 | 1        | 0.8      |         2 |
| Biologiya elmləri  |    0.910891 | 0.87619  | 0.893204 |       105 |
| Coğrafiya          |    0.888889 | 0.941176 | 0.914286 |        17 |
| Filologiya elmləri |    0.971098 | 0.96     | 0.965517 |       175 |
| Fizika             |    0.769231 | 0.882353 | 0.821918 |        34 |
| Fəlsəfə            |    0.875    | 0.5      | 0.636364 |        14 |
| Hüquq elmləri      |    0.966667 | 1        | 0.983051 |        29 |
| Kimya              |    0.855072 | 0.967213 | 0.907692 |        61 |
| Memarlıq           |    0.714286 | 1        | 0.833333 |         5 |
| Mexanika           |    0        | 0        | 0        |         4 |
| Pedaqogika         |    0.958333 | 0.978723 | 0.968421 |        47 |
| Psixologiya        |    0.944444 | 0.944444 | 0.944444 |        18 |
| Riyaziyyat         |    0.921053 | 0.897436 | 0.909091 |        39 |
| Siyasi elmlər      |    0.785714 | 0.88     | 0.830189 |        25 |
| Sosiologiya        |    0.666667 | 1        | 0.8      |         4 |
| Sənətşünaslıq      |    0.84     | 0.893617 | 0.865979 |        47 |
| Tarix              |    0.933333 | 0.897436 | 0.915033 |        78 |
| Texnika elmləri    |    0.894737 | 0.817308 | 0.854271 |       104 |
| Tibb elmləri       |    0.935484 | 0.97973  | 0.957096 |       148 |
| Yer elmləri        |    0.846154 | 0.846154 | 0.846154 |        13 |
| İqtisad elmləri    |    0.973684 | 0.973684 | 0.973684 |       152 |
| Əczaçılıq elmləri  |    0        | 0        | 0        |         4 |
| macro avg          |    0.78972  | 0.828273 | 0.80217  |      1152 |
| weighted avg       |    0.911546 | 0.915799 | 0.912067 |      1152 |

### Framework versions

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