metadata
base_model: SpanBERT/spanbert-large-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: sapect_complaint_spanbert
results: []
sapect_complaint_spanbert
This model is a fine-tuned version of SpanBERT/spanbert-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1905
- F1: 0.7365
- Roc Auc: 0.8250
- Accuracy: 0.5052
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.284 | 1.0 | 582 | 0.2261 | 0.6543 | 0.7733 | 0.3720 |
| 0.2063 | 2.0 | 1164 | 0.1965 | 0.7113 | 0.8003 | 0.4338 |
| 0.1822 | 3.0 | 1746 | 0.1935 | 0.7197 | 0.8062 | 0.4416 |
| 0.1632 | 4.0 | 2328 | 0.1918 | 0.7325 | 0.8210 | 0.4897 |
| 0.1408 | 5.0 | 2910 | 0.1905 | 0.7365 | 0.8250 | 0.5052 |
Framework versions
- Transformers 4.41.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1