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--- |
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license: apache-2.0 |
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base_model: sentence-transformers/LaBSE |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: news_classifier_ft |
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results: [] |
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datasets: |
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- data-silence/rus_news_classifier |
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pipeline_tag: text-classification |
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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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should probably proofread and complete it, then remove this comment. --> |
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# news_classifier_ft |
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This model is a fine-tuned version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3820 |
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- Accuracy: 0.9029 |
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- F1: 0.9025 |
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- Precision: 0.9030 |
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- Recall: 0.9029 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.3544 | 1.0 | 3596 | 0.3517 | 0.8861 | 0.8860 | 0.8915 | 0.8861 | |
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| 0.2738 | 2.0 | 7192 | 0.3190 | 0.8995 | 0.8987 | 0.9025 | 0.8995 | |
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| 0.19 | 3.0 | 10788 | 0.3524 | 0.9016 | 0.9015 | 0.9019 | 0.9016 | |
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| 0.1402 | 4.0 | 14384 | 0.3820 | 0.9029 | 0.9025 | 0.9030 | 0.9029 | |
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| 0.1055 | 5.0 | 17980 | 0.4399 | 0.9022 | 0.9018 | 0.9024 | 0.9022 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
