finetuned-Sentiment-classfication-BERT-model
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3184
- Rmse: 0.3708
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse |
|---|---|---|---|---|
| 0.7279 | 2.72 | 500 | 0.3684 | 0.4686 |
| 0.1642 | 5.43 | 1000 | 0.3184 | 0.3708 |
| 0.0484 | 8.15 | 1500 | 0.3478 | 0.3357 |
| 0.0203 | 10.86 | 2000 | 0.4048 | 0.3311 |
| 0.0112 | 13.58 | 2500 | 0.4055 | 0.3270 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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Model tree for slickdata/finetuned-Sentiment-classfication-BERT-model
Base model
google-bert/bert-base-cased