Introduction-greeting-EN
This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
Model description
label 0: Introduction and label 1: Greeting
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9966 | 222 | 0.0281 | 0.9947 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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the model is not deployed on the HF Inference API.
Model tree for Hemg/Introduction-greeting-EN
Base model
google-bert/bert-base-uncased