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--- |
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library_name: transformers |
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license: mit |
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base_model: mateiaassAI/teacher_ag-news |
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tags: |
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- generated_from_trainer |
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datasets: |
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- moroco |
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metrics: |
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- f1 |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: teacher_agnews_moroco-demo |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: moroco |
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type: moroco |
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config: moroco |
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split: validation |
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args: moroco |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.8679107737455669 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8549231548724877 |
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- name: Precision |
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type: precision |
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value: 0.8702091440403067 |
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- name: Recall |
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type: recall |
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value: 0.8671379372847562 |
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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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# teacher_agnews_moroco-demo |
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This model is a fine-tuned version of [mateiaassAI/teacher_ag-news](https://huggingface.co/mateiaassAI/teacher_ag-news) on the moroco dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0995 |
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- F1: 0.8679 |
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- Roc Auc: None |
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- Accuracy: 0.8549 |
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- Precision: 0.8702 |
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- Recall: 0.8671 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:---------:|:------:| |
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| 0.1183 | 1.0 | 1358 | 0.1007 | 0.8613 | None | 0.8500 | 0.8751 | 0.8528 | |
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| 0.0811 | 2.0 | 2716 | 0.0991 | 0.8688 | None | 0.8546 | 0.8791 | 0.8590 | |
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| 0.0567 | 3.0 | 4074 | 0.0995 | 0.8679 | None | 0.8549 | 0.8702 | 0.8671 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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