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

# green_as_train_context_roberta-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: 1.4371
- Val Accuracy: 0.8913
- Val Precision: 0.7554
- Val Recall: 0.5910
- Val F1: 0.6632

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------------:|:-------------:|:----------:|:------:|
| 0.1908        | 1.0   | 1012  | 0.4035          | 0.8904       | 0.7844        | 0.5448     | 0.6430 |
| 0.152         | 2.0   | 2024  | 0.4631          | 0.8930       | 0.7440        | 0.6235     | 0.6784 |
| 0.12          | 3.0   | 3036  | 0.5046          | 0.8879       | 0.7028        | 0.6605     | 0.6810 |
| 0.0757        | 4.0   | 4048  | 0.7762          | 0.8902       | 0.7438        | 0.6003     | 0.6644 |
| 0.0557        | 5.0   | 5060  | 0.8961          | 0.8846       | 0.7273        | 0.5802     | 0.6455 |
| 0.0319        | 6.0   | 6072  | 0.8864          | 0.8916       | 0.7338        | 0.6296     | 0.6777 |
| 0.0235        | 7.0   | 7084  | 0.8025          | 0.8902       | 0.7348        | 0.6157     | 0.6700 |
| 0.0125        | 8.0   | 8096  | 1.1034          | 0.8916       | 0.7559        | 0.5926     | 0.6644 |
| 0.0114        | 9.0   | 9108  | 1.1414          | 0.8882       | 0.7422        | 0.5864     | 0.6552 |
| 0.0147        | 10.0  | 10120 | 1.2555          | 0.8902       | 0.7401        | 0.6065     | 0.6667 |
| 0.0068        | 11.0  | 11132 | 1.2923          | 0.8879       | 0.7526        | 0.5679     | 0.6473 |
| 0.0112        | 12.0  | 12144 | 1.3150          | 0.8890       | 0.8024        | 0.5139     | 0.6265 |
| 0.0059        | 13.0  | 13156 | 1.1883          | 0.8899       | 0.7396        | 0.6049     | 0.6655 |
| 0.0056        | 14.0  | 14168 | 1.3822          | 0.8871       | 0.7824        | 0.5216     | 0.6259 |
| 0.0029        | 15.0  | 15180 | 1.4309          | 0.8888       | 0.7741        | 0.5448     | 0.6395 |
| 0.0021        | 16.0  | 16192 | 1.3541          | 0.8916       | 0.7529        | 0.5972     | 0.6661 |
| 0.004         | 17.0  | 17204 | 1.3666          | 0.8907       | 0.7384        | 0.6142     | 0.6706 |
| 0.0022        | 18.0  | 18216 | 1.4396          | 0.8896       | 0.7525        | 0.5818     | 0.6562 |
| 0.0028        | 19.0  | 19228 | 1.4340          | 0.8910       | 0.7539        | 0.5910     | 0.6626 |
| 0.0001        | 20.0  | 20240 | 1.4371          | 0.8913       | 0.7554        | 0.5910     | 0.6632 |


### Framework versions

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