Noorrabie/shared-task_content_bert

1---2library_name: transformers3base_model: aubmindlab/bert-base-arabertv024tags:5- generated_from_trainer6metrics:7- accuracy8model-index:9- name: shared-task_content_bert10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# shared-task_content_bert17 18This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.19It achieves the following results on the evaluation set:20- Loss: 1.616621- Macro F1: 0.523822- Macro Precision: 0.550623- Macro Recall: 0.508824- Accuracy: 0.537325 26## Model description27 28More information needed29 30## Intended uses & limitations31 32More information needed33 34## Training and evaluation data35 36More information needed37 38## Training procedure39 40### Training hyperparameters41 42The following hyperparameters were used during training:43- learning_rate: 5e-0544- train_batch_size: 6445- eval_batch_size: 1646- seed: 4247- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments48- lr_scheduler_type: linear49- num_epochs: 650 51### Training results52 53| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy |54|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|55| 1.3557        | 1.0   | 857  | 1.1959          | 0.5085   | 0.5507          | 0.4906       | 0.5293   |56| 1.006         | 2.0   | 1714 | 1.1857          | 0.5130   | 0.5522          | 0.5042       | 0.5339   |57| 0.8063        | 3.0   | 2571 | 1.2605          | 0.5181   | 0.5385          | 0.5079       | 0.5321   |58| 0.6613        | 4.0   | 3428 | 1.3541          | 0.5206   | 0.5486          | 0.5064       | 0.5346   |59| 0.5106        | 5.0   | 4285 | 1.5204          | 0.5151   | 0.5460          | 0.4981       | 0.5304   |60| 0.4373        | 6.0   | 5142 | 1.6166          | 0.5238   | 0.5506          | 0.5088       | 0.5373   |61 62 63### Framework versions64 65- Transformers 4.53.066- Pytorch 2.6.0+cu12467- Datasets 2.14.468- Tokenizers 0.21.269