| --- |
| 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 |
