---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-base_auditor_sentiment
  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. -->

# roberta-base_auditor_sentiment

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5356
- Accuracy: 0.8554
- Precision: 0.8224
- Recall: 0.8722
- F1: 0.8414

## 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: 5e-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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4217        | 1.0   | 485  | 0.6358          | 0.8223   | 0.8142    | 0.8135 | 0.8134 |
| 0.6538        | 2.0   | 970  | 0.6491          | 0.8388   | 0.8584    | 0.8025 | 0.8192 |
| 0.3961        | 3.0   | 1455 | 0.5356          | 0.8554   | 0.8224    | 0.8722 | 0.8414 |
| 0.1121        | 4.0   | 1940 | 0.7393          | 0.8512   | 0.8414    | 0.8477 | 0.8428 |
| 0.0192        | 5.0   | 2425 | 0.7233          | 0.8698   | 0.8581    | 0.8743 | 0.8657 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1