metadata
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: finetuned-Sentiment-classfication-BERT-model
results: []
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: 0.6056
- Rmse: 0.6890
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse |
|---|---|---|---|---|
| 0.7754 | 2.0 | 500 | 0.6056 | 0.6890 |
| 0.3975 | 4.0 | 1000 | 0.6982 | 0.6452 |
| 0.1308 | 6.0 | 1500 | 1.0715 | 0.6643 |
| 0.0526 | 8.0 | 2000 | 1.3439 | 0.6571 |
| 0.0241 | 10.0 | 2500 | 1.4676 | 0.6695 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3