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

# green_as_train_context_roberta-large

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: 0.8427
- Accuracy: 0.8885
- Recall: 0.5802
- F1: 0.6533

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| 0.1927        | 1.0   | 1012 | 0.3691          | 0.8916   | 0.5864 | 0.6620 |
| 0.1417        | 2.0   | 2024 | 0.4204          | 0.8944   | 0.6281 | 0.6829 |
| 0.0954        | 3.0   | 3036 | 0.5585          | 0.8932   | 0.6111 | 0.6746 |
| 0.0447        | 4.0   | 4048 | 0.7888          | 0.8890   | 0.5849 | 0.6563 |
| 0.0217        | 5.0   | 5060 | 0.8427          | 0.8885   | 0.5802 | 0.6533 |


### Framework versions

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