---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
model-index:
- name: clarioscope-insurance-v1
  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. -->

# clarioscope-insurance-v1

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0312
- Macro F1: 0.9571
- Weighted F1: 0.9706

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Weighted F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|
| 0.0304        | 1.0   | 1011 | 0.0343          | 0.9486   | 0.9624      |
| 0.0147        | 2.0   | 2022 | 0.0345          | 0.9537   | 0.9682      |
| 0.0223        | 3.0   | 3033 | 0.0312          | 0.9571   | 0.9706      |
| 0.0082        | 4.0   | 4044 | 0.0325          | 0.9562   | 0.9704      |
| 0.0152        | 5.0   | 5055 | 0.0328          | 0.9563   | 0.9706      |


### Framework versions

- Transformers 5.8.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2