metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: email_answer_extraction
results: []
email_answer_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: 0.0388
- Precision: 0.3571
- Recall: 0.5769
- F1: 0.4412
- Accuracy: 0.9859
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 |
|---|---|---|---|---|---|---|---|
| 0.4874 | 1.0 | 32 | 0.0956 | 0.0339 | 0.0769 | 0.0471 | 0.9714 |
| 0.1951 | 2.0 | 64 | 0.0448 | 0.2115 | 0.4231 | 0.2821 | 0.9829 |
| 0.1086 | 3.0 | 96 | 0.0384 | 0.3556 | 0.6154 | 0.4507 | 0.9857 |
| 0.0552 | 4.0 | 128 | 0.0388 | 0.3571 | 0.5769 | 0.4412 | 0.9859 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.16.0
- Tokenizers 0.15.0