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ModeloFT1-v1
adriansanz/ModeloFT1-v1
ModeloFT1-v1 is a text classification model from adriansanz. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Apr 22, 2024
- Updated
- Apr 22, 2024
- SHA
- 72fee6af
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
stocks
This model is a fine-tuned version of projecte-aina/roberta-base-ca-v2-cawikitc on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6639
- Accuracy: 0.7637
- Precision: 0.5304
- Recall: 0.4710
- F1: 0.4778
- Ratio: 0.7903
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: 10
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- lr_scheduler_warmup_steps: 4
- num_epochs: 1
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
|---|---|---|---|---|---|---|---|---|
| 0.8468 | 0.07 | 10 | 0.8350 | 0.6185 | 0.3093 | 0.5 | 0.3822 | 1.0 |
| 0.7922 | 0.14 | 20 | 0.8314 | 0.6185 | 0.3093 | 0.5 | 0.3822 | 1.0 |
| 0.8005 | 0.21 | 30 | 0.8059 | 0.6169 | 0.2060 | 0.3325 | 0.2544 | 0.9984 |
| 0.8038 | 0.28 | 40 | 0.7907 | 0.6185 | 0.3093 | 0.5 | 0.3822 | 1.0 |
| 0.7846 | 0.34 | 50 | 0.8060 | 0.6185 | 0.3093 | 0.5 | 0.3822 | 1.0 |
| 0.7539 | 0.41 | 60 | 0.7573 | 0.6274 | 0.5024 | 0.3422 | 0.2763 | 0.9847 |
| 0.725 | 0.48 | 70 | 0.8018 | 0.7435 | 0.4978 | 0.4906 | 0.4940 | 0.5847 |
| 0.6842 | 0.55 | 80 | 0.8437 | 0.7419 | 0.5035 | 0.4795 | 0.4901 | 0.6444 |
| 0.7415 | 0.62 | 90 | 0.7783 | 0.7468 | 0.5006 | 0.4832 | 0.4909 | 0.6444 |
| 0.6303 | 0.69 | 100 | 0.7194 | 0.7452 | 0.5009 | 0.4723 | 0.4808 | 0.7040 |
| 0.6844 | 0.76 | 110 | 0.7137 | 0.7702 | 0.5106 | 0.4996 | 0.5044 | 0.6468 |
| 0.699 | 0.83 | 120 | 0.6666 | 0.7806 | 0.5159 | 0.5039 | 0.5084 | 0.6653 |
| 0.7229 | 0.9 | 130 | 0.6636 | 0.7629 | 0.5233 | 0.4730 | 0.4799 | 0.775 |
| 0.6555 | 0.97 | 140 | 0.6646 | 0.7637 | 0.5312 | 0.4707 | 0.4775 | 0.7919 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Apr 22, 2024
- Updated
- Apr 22, 2024