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---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
model-index:
- name: categories-estimation
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. -->
# categories-estimation
This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training Metrics
Step Training Loss Validation Loss F1 Accuracy
100 0.257000 0.432904 0.853367 0.905234
200 0.241600 0.431226 0.848656 0.903030
300 0.242200 0.407710 0.865890 0.908356
400 0.201600 0.375613 0.881634 0.918825
500 0.181400 0.378719 0.879368 0.916988
600 0.168800 0.361804 0.885401 0.920478
## Evaluation Metrics
{'eval_loss': 0.3545467257499695,
'eval_F1': 0.8847876543649995,
'eval_Accuracy': 0.9213957759412305,
'eval_runtime': 14.8305,
'eval_samples_per_second': 367.149,
'eval_steps_per_second': 45.919,
'epoch': 1.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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