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

# paper_feedback_intent

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: 0.3621
- Accuracy: 0.9302
- Precision: 0.9307
- Recall: 0.9302
- F1: 0.9297

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9174        | 1.0   | 11   | 0.7054          | 0.7907   | 0.7903    | 0.7907 | 0.7861 |
| 0.6917        | 2.0   | 22   | 0.4665          | 0.8140   | 0.8134    | 0.8140 | 0.8118 |
| 0.4276        | 3.0   | 33   | 0.3326          | 0.9070   | 0.9065    | 0.9070 | 0.9041 |
| 0.2656        | 4.0   | 44   | 0.3286          | 0.9070   | 0.9065    | 0.9070 | 0.9041 |
| 0.1611        | 5.0   | 55   | 0.3044          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.1025        | 6.0   | 66   | 0.3227          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.0799        | 7.0   | 77   | 0.3216          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.0761        | 8.0   | 88   | 0.3529          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.0479        | 9.0   | 99   | 0.3605          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.0358        | 10.0  | 110  | 0.3621          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6