Downloads · 30 days
9
3% of all-time downloads
roberta-pundec
LendeaViva/roberta-pundec
roberta-pundec is a token classification model from LendeaViva. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
261
Public
Parameters
81.5M
326 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors326 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Apr 18, 2024
- Updated
- Apr 18, 2024
- SHA
- c40e6f75
Try a prompt
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. -->
RoBERTa_PT_BR_PosNeg_2
This model is a fine-tuned version of josu/roberta-pt-br on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1140
- Precision: 0.4694
- Recall: 0.4181
- F1: 0.4423
- Accuracy: 0.9480
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1161 | 2.0040 | 500 | 0.1242 | 0.4423 | 0.3870 | 0.4128 | 0.9423 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- Created
- Apr 18, 2024
- Updated
- Apr 18, 2024