---
base_model: SpanBERT/spanbert-large-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: sapect_complaint_spanbert
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# sapect_complaint_spanbert

This model is a fine-tuned version of [SpanBERT/spanbert-large-cased](https://huggingface.co/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