metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: email_question_extraction
results: []
email_question_extraction
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0071
- Precision: 0.4595
- Recall: 0.8095
- F1: 0.5862
- Accuracy: 0.9978
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0653 | 1.0 | 73 | 0.0097 | 0.5156 | 0.7857 | 0.6226 | 0.9963 |
| 0.0307 | 2.0 | 146 | 0.0056 | 0.5263 | 0.7143 | 0.6061 | 0.9986 |
| 0.027 | 3.0 | 219 | 0.0081 | 0.4667 | 0.8333 | 0.5983 | 0.9971 |
| 0.0046 | 4.0 | 292 | 0.0071 | 0.4595 | 0.8095 | 0.5862 | 0.9978 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.16.0
- Tokenizers 0.15.0