---
language:
- en
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
datasets:
- schone-affiliation
model-index:
- name: final
  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. -->

# final

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the GLUE SCHONE_AFF dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1011
- Roc Auc: 0.9877

## 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: 128
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Roc Auc |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2128        | 0.9985 | 332  | 0.1760          | 0.9613  |
| 0.184         | 2.0    | 665  | 0.1493          | 0.9730  |
| 0.1592        | 2.9985 | 997  | 0.1257          | 0.9811  |
| 0.1464        | 4.0    | 1330 | 0.1069          | 0.9861  |
| 0.1236        | 4.9925 | 1660 | 0.1011          | 0.9877  |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1