---
library_name: transformers
license: agpl-3.0
base_model: RonTon05/model_content_V2_test
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: MTL_Full_Finetuning
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# MTL_Full_Finetuning

This model is a fine-tuned version of [RonTon05/model_content_V2_test](https://huggingface.co/RonTon05/model_content_V2_test) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9761
- F1 Task1: 0.9899
- F1 Task2: 0.7639
- Acc Task1: 0.9943
- Acc Task2: 0.7585
- F1: 0.8769
- F1 Macro: 0.8769

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Task1 | F1 Task2 | Acc Task1 | Acc Task2 | F1     | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:---------:|:------:|:--------:|
| 1.6340        | 1.0   | 275  | 1.2347          | 0.9871   | 0.2939   | 0.9927    | 0.5834    | 0.6405 | 0.6405   |
| 1.0585        | 2.0   | 550  | 0.9700          | 0.9898   | 0.5208   | 0.9943    | 0.6823    | 0.7553 | 0.7553   |
| 0.8066        | 3.0   | 825  | 0.9386          | 0.9852   | 0.6708   | 0.9916    | 0.7146    | 0.8280 | 0.8280   |
| 0.6469        | 4.0   | 1100 | 0.8487          | 0.9923   | 0.6977   | 0.9957    | 0.7294    | 0.8450 | 0.8450   |
| 0.5103        | 5.0   | 1375 | 0.8253          | 0.9887   | 0.7354   | 0.9936    | 0.7532    | 0.8620 | 0.8620   |
| 0.3982        | 6.0   | 1650 | 0.8406          | 0.9891   | 0.7503   | 0.9939    | 0.7546    | 0.8697 | 0.8697   |
| 0.3155        | 7.0   | 1925 | 0.8892          | 0.9891   | 0.7520   | 0.9939    | 0.7501    | 0.8705 | 0.8705   |
| 0.2617        | 8.0   | 2200 | 0.9669          | 0.9895   | 0.7513   | 0.9941    | 0.7503    | 0.8704 | 0.8704   |
| 0.2198        | 9.0   | 2475 | 0.9501          | 0.9899   | 0.7630   | 0.9943    | 0.7562    | 0.8764 | 0.8764   |
| 0.1932        | 10.0  | 2750 | 0.9761          | 0.9899   | 0.7639   | 0.9943    | 0.7585    | 0.8769 | 0.8769   |


### Framework versions

- Transformers 5.10.1
- Pytorch 2.7.1+cu118
- Datasets 4.8.5
- Tokenizers 0.22.2