---
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- f1
model-index:
- name: non_green_as_train_contextroberta-large_final
  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. -->

# non_green_as_train_contextroberta-large_final

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1008
- Accuracy: 0.9769
- Recall: 0.6932
- F1: 0.6943

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
| 0.0664        | 1.0   | 7739  | 0.0862          | 0.9658   | 0.8042 | 0.6396 |
| 0.0577        | 2.0   | 15478 | 0.1060          | 0.9768   | 0.6741 | 0.6869 |
| 0.0337        | 3.0   | 23217 | 0.1008          | 0.9769   | 0.6932 | 0.6943 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2