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---
license: mit
base_model: neuralmind/bert-large-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: google-play-sentiment-analysis
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. -->
# google-play-sentiment-analysis
This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0987
- Accuracy: 0.3229
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8592 | 1.0 | 1200 | 0.8029 | 0.6279 |
| 0.9076 | 2.0 | 2400 | 1.1314 | 0.3229 |
| 1.1221 | 3.0 | 3600 | 1.1170 | 0.3229 |
| 1.1211 | 4.0 | 4800 | 1.1020 | 0.3362 |
| 1.115 | 5.0 | 6000 | 1.1015 | 0.3408 |
| 1.12 | 6.0 | 7200 | 1.0989 | 0.3408 |
| 1.1153 | 7.0 | 8400 | 1.0989 | 0.3408 |
| 1.1123 | 8.0 | 9600 | 1.0993 | 0.3408 |
| 1.1125 | 9.0 | 10800 | 1.0987 | 0.3408 |
| 1.1109 | 10.0 | 12000 | 1.0987 | 0.3229 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|