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roberta-base-ca-finetuned-tecla
JonatanGk/roberta-base-ca-finetuned-tecla
roberta-base-ca-finetuned-tecla is a text classification model from JonatanGk. 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
- Mar 2, 2022
- Updated
- Oct 22, 2021
- SHA
- 9fd0f84b
Try a prompt
Datasets
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. -->
roberta-base-ca-finetuned-mnli
This model is a fine-tuned version of BSC-TeMU/roberta-base-ca on the tecla dataset. It achieves the following results on the evaluation set:
- Loss: 0.9354
- Accuracy: 0.7362
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8465 | 1.0 | 6888 | 0.8222 | 0.6990 |
| 0.6966 | 2.0 | 13776 | 0.7872 | 0.7157 |
| 0.5643 | 3.0 | 20664 | 0.8060 | 0.7268 |
| 0.4435 | 4.0 | 27552 | 0.8470 | 0.7333 |
| 0.3206 | 5.0 | 34440 | 0.9354 | 0.7362 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Oct 22, 2021