google-play-sentiment-analysis

README.md

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+---
+license: mit
+base_model: neuralmind/bert-base-portuguese-cased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+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-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.6324
+- F1: 0.5277
+
+## 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: 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 0.7056        | 1.0   | 1125  | 1.5127          | 0.4766 |
+| 0.7472        | 2.0   | 2250  | 1.4296          | 0.5148 |
+| 0.5266        | 3.0   | 3375  | 1.6938          | 0.5262 |
+| 0.3887        | 4.0   | 4500  | 2.1185          | 0.5176 |
+| 0.3078        | 5.0   | 5625  | 2.5383          | 0.5229 |
+| 0.2286        | 6.0   | 6750  | 3.0566          | 0.5107 |
+| 0.1718        | 7.0   | 7875  | 3.3369          | 0.5248 |
+| 0.1324        | 8.0   | 9000  | 3.4615          | 0.5255 |
+| 0.1372        | 9.0   | 10125 | 3.5526          | 0.5221 |
+| 0.1095        | 10.0  | 11250 | 3.6324          | 0.5277 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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