---
library_name: transformers
license: agpl-3.0
base_model: RonTon05/model_content_V2_test
tags:
- generated_from_trainer
model-index:
- name: New_MTL_Full_Finetuning_OverSampling
  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. -->

# New_MTL_Full_Finetuning_OverSampling

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: 0.4517
- F1 Task1: 0.9727
- F1 Task2: 0.7492
- Acc Task1: 0.9789
- Acc Task2: 0.9160
- F1 Macro: 0.8609

## 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: 128
- eval_batch_size: 128
- 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 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 261
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Task1 | F1 Task2 | Acc Task1 | Acc Task2 | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:---------:|:--------:|
| 0.9477        | 1.0   | 261  | 0.6483          | 0.9686   | 0.3580   | 0.9757    | 0.8208    | 0.6633   |
| 0.5012        | 2.0   | 522  | 0.4314          | 0.9709   | 0.7120   | 0.9774    | 0.8852    | 0.8414   |
| 0.3632        | 3.0   | 783  | 0.3812          | 0.9722   | 0.7348   | 0.9786    | 0.9047    | 0.8535   |
| 0.2974        | 4.0   | 1044 | 0.3800          | 0.9742   | 0.7434   | 0.9800    | 0.9074    | 0.8588   |
| 0.2496        | 5.0   | 1305 | 0.3895          | 0.9728   | 0.7440   | 0.9790    | 0.9115    | 0.8584   |
| 0.2106        | 6.0   | 1566 | 0.4031          | 0.9731   | 0.7459   | 0.9791    | 0.9108    | 0.8595   |
| 0.1790        | 7.0   | 1827 | 0.4297          | 0.9734   | 0.7460   | 0.9794    | 0.9157    | 0.8597   |
| 0.1574        | 8.0   | 2088 | 0.4305          | 0.9731   | 0.7487   | 0.9792    | 0.9180    | 0.8609   |
| 0.1412        | 9.0   | 2349 | 0.4515          | 0.9743   | 0.7511   | 0.9801    | 0.9172    | 0.8627   |
| 0.1321        | 10.0  | 2610 | 0.4517          | 0.9727   | 0.7492   | 0.9789    | 0.9160    | 0.8609   |


### Framework versions

- Transformers 5.17.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.1
- Tokenizers 0.23.2