|
--- |
|
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 |
|
|
