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library_name: transformers
license: agpl-3.0
base_model: ttqdunggg/finetune_cls_vs_content_ronbackbone_100k
tags:
- generated_from_trainer
model-index:
- name: 2_task_v2_new2labels
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. -->
# 2_task_v2_new2labels
This model is a fine-tuned version of [ttqdunggg/finetune_cls_vs_content_ronbackbone_100k](https://huggingface.co/ttqdunggg/finetune_cls_vs_content_ronbackbone_100k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- F1 New: 0.7766
- Acc New: 0.7868
## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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: cosine
- lr_scheduler_warmup_steps: 80
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 New | Acc New |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 0.6547 | 1.0 | 40 | nan | 0.6830 | 0.7426 |
| 0.5695 | 2.0 | 80 | nan | 0.7176 | 0.7574 |
| 0.5323 | 3.0 | 120 | nan | 0.7236 | 0.75 |
| 0.5104 | 4.0 | 160 | nan | 0.7527 | 0.7647 |
| 0.4958 | 5.0 | 200 | nan | 0.7654 | 0.7868 |
| 0.4795 | 6.0 | 240 | nan | 0.7405 | 0.75 |
| 0.4719 | 7.0 | 280 | nan | 0.7874 | 0.8015 |
| 0.4584 | 8.0 | 320 | nan | 0.7874 | 0.8015 |
| 0.4528 | 9.0 | 360 | nan | 0.7612 | 0.7721 |
| 0.4434 | 10.0 | 400 | nan | 0.7766 | 0.7868 |
| 0.4443 | 11.0 | 440 | nan | 0.7961 | 0.8088 |
| 0.4358 | 12.0 | 480 | nan | 0.7836 | 0.7941 |
| 0.4393 | 13.0 | 520 | nan | 0.7696 | 0.7794 |
| 0.4391 | 14.0 | 560 | nan | 0.7766 | 0.7868 |
| 0.4265 | 15.0 | 600 | nan | 0.7836 | 0.7941 |
| 0.4270 | 16.0 | 640 | nan | 0.7766 | 0.7868 |
### Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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