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@@ -11,6 +11,10 @@ metrics:
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  model-index:
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  - name: xlm-roberta-large-azsci-topics
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  results: []
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,7 +22,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # xlm-roberta-large-azsci-topics
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- This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.4012
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  - Precision: 0.9115
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  - F1: 0.9121
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  - Accuracy: 0.9158
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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  ## Training procedure
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  ### Training hyperparameters
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  | 0.3135 | 4.0 | 1152 | 0.4177 | 0.9043 | 0.9080 | 0.9047 | 0.9080 |
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  | 0.3135 | 5.0 | 1440 | 0.4012 | 0.9115 | 0.9158 | 0.9121 | 0.9158 |
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  ### Framework versions
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  - Transformers 4.38.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  model-index:
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  - name: xlm-roberta-large-azsci-topics
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  results: []
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+ datasets:
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+ - hajili/azsci_topics
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+ language:
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+ - az
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # xlm-roberta-large-azsci-topics
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+ 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.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.4012
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  - Precision: 0.9115
 
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  - F1: 0.9121
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  - Accuracy: 0.9158
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  ## Training procedure
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  ### Training hyperparameters
 
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  | 0.3135 | 4.0 | 1152 | 0.4177 | 0.9043 | 0.9080 | 0.9047 | 0.9080 |
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  | 0.3135 | 5.0 | 1440 | 0.4012 | 0.9115 | 0.9158 | 0.9121 | 0.9158 |
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+ ### Evaluation results
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+
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+ | Topic | Precision | Recall | F1 | Support |
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+ |:-------------------|------------:|---------:|---------:|----------:|
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+ | Aqrar elmlər | 0.846154 | 0.814815 | 0.830189 | 27 |
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+ | Astronomiya | 0.666667 | 1 | 0.8 | 2 |
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+ | Biologiya elmləri | 0.910891 | 0.87619 | 0.893204 | 105 |
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+ | Coğrafiya | 0.888889 | 0.941176 | 0.914286 | 17 |
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+ | Filologiya elmləri | 0.971098 | 0.96 | 0.965517 | 175 |
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+ | Fizika | 0.769231 | 0.882353 | 0.821918 | 34 |
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+ | Fəlsəfə | 0.875 | 0.5 | 0.636364 | 14 |
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+ | Hüquq elmləri | 0.966667 | 1 | 0.983051 | 29 |
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+ | Kimya | 0.855072 | 0.967213 | 0.907692 | 61 |
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+ | Memarlıq | 0.714286 | 1 | 0.833333 | 5 |
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+ | Mexanika | 0 | 0 | 0 | 4 |
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+ | Pedaqogika | 0.958333 | 0.978723 | 0.968421 | 47 |
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+ | Psixologiya | 0.944444 | 0.944444 | 0.944444 | 18 |
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+ | Riyaziyyat | 0.921053 | 0.897436 | 0.909091 | 39 |
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+ | Siyasi elmlər | 0.785714 | 0.88 | 0.830189 | 25 |
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+ | Sosiologiya | 0.666667 | 1 | 0.8 | 4 |
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+ | Sənətşünaslıq | 0.84 | 0.893617 | 0.865979 | 47 |
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+ | Tarix | 0.933333 | 0.897436 | 0.915033 | 78 |
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+ | Texnika elmləri | 0.894737 | 0.817308 | 0.854271 | 104 |
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+ | Tibb elmləri | 0.935484 | 0.97973 | 0.957096 | 148 |
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+ | Yer elmləri | 0.846154 | 0.846154 | 0.846154 | 13 |
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+ | İqtisad elmləri | 0.973684 | 0.973684 | 0.973684 | 152 |
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+ | Əczaçılıq elmləri | 0 | 0 | 0 | 4 |
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+ | macro avg | 0.78972 | 0.828273 | 0.80217 | 1152 |
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+ | weighted avg | 0.911546 | 0.915799 | 0.912067 | 1152 |
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  ### Framework versions
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  - Transformers 4.38.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.18.0
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+ - Tokenizers 0.15.2