---
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