bert-base-uncased-amazon-reviews-sentiment-analysis
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2344
- Accuracy: 0.9198
- F1: 0.9215
- Precision: 0.9263
- Recall: 0.9167
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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6741 | 1.0 | 47 | 0.6232 | 0.7594 | 0.7097 | 0.9322 | 0.5729 |
| 0.4346 | 2.0 | 94 | 0.3871 | 0.8717 | 0.875 | 0.875 | 0.875 |
| 0.3593 | 3.0 | 141 | 0.2344 | 0.9198 | 0.9215 | 0.9263 | 0.9167 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for ckandemir/bert-base-uncased-amazon-reviews-sentiment-analysis
Base model
google-bert/bert-base-uncased