transformers tensorboard safetensors generated_from_trainer base_model:roberta-large license:mit endpoints_compatible region:us
---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1093
- F1: 0.8624
- Roc Auc: 0.9036
- Accuracy: 0.9395

## 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: 0.001
- 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 289  | 0.1145          | 0.8019 | 0.8592  | 0.9193   |
| 0.1486        | 2.0   | 578  | 0.1079          | 0.8357 | 0.8818  | 0.9294   |
| 0.1486        | 3.0   | 867  | 0.1021          | 0.8511 | 0.8876  | 0.9384   |
| 0.0655        | 4.0   | 1156 | 0.0979          | 0.8428 | 0.8953  | 0.9314   |
| 0.0655        | 5.0   | 1445 | 0.1114          | 0.8686 | 0.9171  | 0.9405   |
| 0.0495        | 6.0   | 1734 | 0.1165          | 0.8429 | 0.8811  | 0.9344   |
| 0.0323        | 7.0   | 2023 | 0.1093          | 0.8624 | 0.9036  | 0.9395   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
