---
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
model-index:
- name: non_green_as_train_contextroberta-large_20e
  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_20e

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: 0.3214
- Val Accuracy: 0.9779
- Val Precision: 0.6893
- Val Recall: 0.7568
- Val F1: 0.7215

## 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: 5e-06
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Val Accuracy | Val Precision | Val Recall | Val F1 |
|:-------------:|:-----:|:------:|:---------------:|:------------:|:-------------:|:----------:|:------:|
| 0.0601        | 1.0   | 7739   | 0.0767          | 0.9763       | 0.6646        | 0.7518     | 0.7055 |
| 0.0493        | 2.0   | 15478  | 0.0995          | 0.9785       | 0.7181        | 0.7094     | 0.7137 |
| 0.0305        | 3.0   | 23217  | 0.1216          | 0.9765       | 0.6670        | 0.7578     | 0.7095 |
| 0.0196        | 4.0   | 30956  | 0.1275          | 0.9786       | 0.7066        | 0.7437     | 0.7247 |
| 0.0161        | 5.0   | 38695  | 0.1521          | 0.9768       | 0.7164        | 0.6398     | 0.6759 |
| 0.0141        | 6.0   | 46434  | 0.1643          | 0.9785       | 0.7103        | 0.7275     | 0.7188 |
| 0.007         | 7.0   | 54173  | 0.1660          | 0.9769       | 0.6739        | 0.7528     | 0.7112 |
| 0.0052        | 8.0   | 61912  | 0.1855          | 0.9783       | 0.7036        | 0.7376     | 0.7202 |
| 0.0048        | 9.0   | 69651  | 0.1845          | 0.9781       | 0.7042        | 0.7255     | 0.7147 |
| 0.0031        | 10.0  | 77390  | 0.2165          | 0.9782       | 0.7225        | 0.6882     | 0.7049 |
| 0.0036        | 11.0  | 85129  | 0.2271          | 0.9783       | 0.7223        | 0.6902     | 0.7059 |
| 0.0029        | 12.0  | 92868  | 0.2345          | 0.9770       | 0.6887        | 0.7144     | 0.7013 |
| 0.0015        | 13.0  | 100607 | 0.2636          | 0.9781       | 0.7307        | 0.6680     | 0.6979 |
| 0.0045        | 14.0  | 108346 | 0.2493          | 0.9781       | 0.6846        | 0.7820     | 0.7301 |
| 0.0005        | 15.0  | 116085 | 0.2563          | 0.9774       | 0.6789        | 0.7639     | 0.7189 |
| 0.0007        | 16.0  | 123824 | 0.2856          | 0.9784       | 0.7193        | 0.7033     | 0.7112 |
| 0.0           | 17.0  | 131563 | 0.2809          | 0.9782       | 0.7136        | 0.7064     | 0.7099 |
| 0.0           | 18.0  | 139302 | 0.3033          | 0.9781       | 0.6957        | 0.7497     | 0.7217 |
| 0.0           | 19.0  | 147041 | 0.3207          | 0.9782       | 0.6909        | 0.7669     | 0.7269 |
| 0.0           | 20.0  | 154780 | 0.3214          | 0.9779       | 0.6893        | 0.7568     | 0.7215 |


### Framework versions

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