---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ACTS_feedback1
  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. -->

# ACTS_feedback1

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: 0.2357
- Accuracy: 0.8936
- Balanced accuracy: 0.8897
- Precision: 0.8951
- Recall: 0.8936
- F1: 0.8915

## 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 | Balanced accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:|
| 1.0881        | 1.0   | 12   | 1.0513          | 0.5532   | 0.5119            | 0.4004    | 0.5532 | 0.4645 |
| 0.9933        | 2.0   | 24   | 0.9257          | 0.5319   | 0.4952            | 0.3852    | 0.5319 | 0.4463 |
| 0.8065        | 3.0   | 36   | 0.7059          | 0.7234   | 0.7295            | 0.7607    | 0.7234 | 0.7184 |
| 0.5504        | 4.0   | 48   | 0.4259          | 0.8511   | 0.8474            | 0.8486    | 0.8511 | 0.8472 |
| 0.3262        | 5.0   | 60   | 0.3703          | 0.8511   | 0.8654            | 0.8624    | 0.8511 | 0.8499 |
| 0.1877        | 6.0   | 72   | 0.2518          | 0.8723   | 0.8731            | 0.8719    | 0.8723 | 0.8703 |
| 0.1094        | 7.0   | 84   | 0.2283          | 0.9362   | 0.9410            | 0.9415    | 0.9362 | 0.9365 |
| 0.0721        | 8.0   | 96   | 0.2246          | 0.9149   | 0.9244            | 0.9233    | 0.9149 | 0.9149 |
| 0.0521        | 9.0   | 108  | 0.2215          | 0.8936   | 0.8897            | 0.8951    | 0.8936 | 0.8915 |
| 0.0455        | 10.0  | 120  | 0.2357          | 0.8936   | 0.8897            | 0.8951    | 0.8936 | 0.8915 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6