| --- |
| library_name: transformers |
| license: agpl-3.0 |
| base_model: RonTon05/model_content_V2_test |
| tags: |
| - generated_from_trainer |
| - text-classification |
| - multi-task-learning |
| model-index: |
| - name: MTL_ATESG_Weighted |
| results: |
| - task: |
| type: text-classification |
| name: "Task 1: Binary Classification" |
| dataset: |
| type: custom |
| name: Validation Set |
| metrics: |
| - type: accuracy |
| value: 0.9939 |
| name: Accuracy |
| - type: f1 |
| value: 0.9892 |
| name: Macro F1 |
| - task: |
| type: text-classification |
| name: "Task 2: 10-class Classification" |
| dataset: |
| type: custom |
| name: Validation Set |
| metrics: |
| - type: accuracy |
| value: 0.7587 |
| name: Accuracy |
| - type: f1 |
| value: 0.7924 |
| name: Macro F1 |
| --- |
| |
| # MTL_ATESG_Weighted |
|
|
| This model is a fine-tuned version of [RonTon05/model_content_V2_test](https://huggingface.co/RonTon05/model_content_V2_test) on a custom multi-task dataset. |
|
|
| ## Training Results |
|
|
| ### TASK 1 — Binary Classification |
| - **Accuracy:** 99.39% |
| - **Macro F1:** 98.92% |
|
|
| | Class | Precision | Recall | F1-Score | Support | |
| | :---: | :---: | :---: | :---: | :---: | |
| | **0** | 0.9986 | 0.9940 | 0.9963 | 3654 | |
| | **1** | 0.9711 | 0.9933 | 0.9820 | 743 | |
| | **Macro Avg** | 0.9848 | 0.9936 | 0.9892 | 4397 | |
| | **Weighted Avg** | 0.9940 | 0.9939 | 0.9939 | 4397 | |
|
|
| ### TASK 2 — 10-class Classification |
| - **Accuracy:** 75.87% |
| - **Macro F1:** 79.24% |
|
|
| | Class | Precision | Recall | F1-Score | Support | |
| | :---: | :---: | :---: | :---: | :---: | |
| | **0** | 0.8114 | 0.6930 | 0.7475 | 329 | |
| | **1** | 0.9487 | 0.8605 | 0.9024 | 43 | |
| | **2** | 0.8743 | 0.9162 | 0.8947 | 167 | |
| | **3** | 0.9585 | 0.9373 | 0.9478 | 271 | |
| | **4** | 0.9400 | 0.8034 | 0.8664 | 117 | |
| | **5** | 0.6403 | 0.7860 | 0.7057 | 958 | |
| | **6** | 0.7981 | 0.7837 | 0.7908 | 1387 | |
| | **7** | 0.5900 | 0.5364 | 0.5619 | 110 | |
| | **8** | 0.8450 | 0.8074 | 0.8258 | 135 | |
| | **9** | 0.7299 | 0.6386 | 0.6812 | 880 | |
| | **Macro Avg** | 0.8136 | 0.7762 | 0.7924 | 4397 | |
| | **Weighted Avg** | 0.7653 | 0.7587 | 0.7592 | 4397 | |
|
|
| --- |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 128 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 256 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 1035 |
| - num_epochs: 50 |
|
|
| ### Framework versions |
|
|
| - Transformers 5.10.2 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 5.0.0 |
| - Tokenizers 0.22.2 |
