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

# temp_model_outputdir

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: 0.3571
- Precision: 0.9390
- Recall: 0.9355
- F1: 0.9315
- Accuracy: 0.9355

## 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: 2.2e-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: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step  | Accuracy | F1     | Validation Loss | Precision | Recall |
|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:|
| 1.9118        | 1.0   | 1511  | 0.8173   | 0.8042 | 0.7125          | 0.8320    | 0.8173 |
| 0.6271        | 2.0   | 3022  | 0.8402   | 0.8360 | 0.6493          | 0.8535    | 0.8402 |
| 0.5214        | 3.0   | 4533  | 0.8342   | 0.8285 | 0.7902          | 0.8391    | 0.8342 |
| 0.7385        | 4.0   | 6044  | 0.8769   | 0.8724 | 0.5748          | 0.8879    | 0.8769 |
| 0.6674        | 5.0   | 7555  | 0.8640   | 0.8602 | 0.5157          | 0.8802    | 0.8640 |
| 0.4279        | 6.0   | 9066  | 0.9077   | 0.9029 | 0.4802          | 0.9148    | 0.9077 |
| 0.5507        | 7.0   | 10577 | 0.3693   | 0.9371 | 0.9332          | 0.9288    | 0.9332 |
| 0.2703        | 8.0   | 12088 | 0.3571   | 0.9390 | 0.9355          | 0.9315    | 0.9355 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0