---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-large-finetuned-ours-DS
  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-large-finetuned-ours-DS

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8358
- Accuracy: 0.71
- Precision: 0.6611
- Recall: 0.6691
- F1: 0.6570

## 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: 16
- eval_batch_size: 16
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0561        | 0.99  | 99   | 0.8773          | 0.615    | 0.4054    | 0.5584 | 0.4591 |
| 0.762         | 1.98  | 198  | 0.6514          | 0.715    | 0.6735    | 0.6672 | 0.6588 |
| 0.5661        | 2.97  | 297  | 0.6806          | 0.71     | 0.6764    | 0.6608 | 0.6435 |
| 0.3699        | 3.96  | 396  | 0.8358          | 0.71     | 0.6611    | 0.6691 | 0.6570 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1