finetuning-sentiment-model-1000-samples
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6955
- eval_accuracy: 0.7067
- eval_f1: 0.6384
- eval_runtime: 3.7307
- eval_samples_per_second: 80.415
- eval_steps_per_second: 5.093
- step: 0
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Model tree for alexandreacff/finetuning-sentiment-model-1000-samples
Base model
neuralmind/bert-base-portuguese-cased