---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: newsdiscourse-model-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. -->

# newsdiscourse-model-large

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: 1.5899
- F1: 0.1975

## 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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.14  | 100  | 1.9895          | 0.0487 |
| No log        | 0.28  | 200  | 2.0130          | 0.0512 |
| No log        | 0.43  | 300  | 1.9527          | 0.0512 |
| No log        | 0.57  | 400  | 1.9605          | 0.0487 |
| 2.0539        | 0.71  | 500  | 1.9854          | 0.0618 |
| 2.0539        | 0.85  | 600  | 1.7978          | 0.1242 |
| 2.0539        | 1.0   | 700  | 1.7291          | 0.1373 |
| 2.0539        | 1.14  | 800  | 1.9082          | 0.0487 |
| 2.0539        | 1.28  | 900  | 1.9300          | 0.0487 |
| 1.9096        | 1.42  | 1000 | 1.7186          | 0.1414 |
| 1.9096        | 1.57  | 1100 | 1.7304          | 0.1399 |
| 1.9096        | 1.71  | 1200 | 1.7281          | 0.1363 |
| 1.9096        | 1.85  | 1300 | 1.8452          | 0.0576 |
| 1.9096        | 1.99  | 1400 | 1.7180          | 0.1519 |
| 1.7842        | 2.14  | 1500 | 1.7450          | 0.1525 |
| 1.7842        | 2.28  | 1600 | 1.7752          | 0.1344 |
| 1.7842        | 2.42  | 1700 | 1.7548          | 0.1506 |
| 1.7842        | 2.56  | 1800 | 1.7185          | 0.1536 |
| 1.7842        | 2.71  | 1900 | 1.6870          | 0.1536 |
| 1.7227        | 2.85  | 2000 | 1.7336          | 0.1536 |
| 1.7227        | 2.99  | 2100 | 1.7217          | 0.1490 |
| 1.7227        | 3.13  | 2200 | 1.7213          | 0.1482 |
| 1.7227        | 3.28  | 2300 | 1.7482          | 0.1435 |
| 1.7227        | 3.42  | 2400 | 1.7559          | 0.1456 |
| 1.7441        | 3.56  | 2500 | 1.7324          | 0.1406 |
| 1.7441        | 3.7   | 2600 | 1.6977          | 0.1484 |
| 1.7441        | 3.85  | 2700 | 1.6276          | 0.1839 |
| 1.7441        | 3.99  | 2800 | 1.6109          | 0.1876 |
| 1.7441        | 4.13  | 2900 | 1.6359          | 0.2181 |
| 1.6515        | 4.27  | 3000 | 1.6463          | 0.1792 |
| 1.6515        | 4.42  | 3100 | 1.6397          | 0.1828 |
| 1.6515        | 4.56  | 3200 | 1.6189          | 0.1837 |
| 1.6515        | 4.7   | 3300 | 1.6096          | 0.1875 |
| 1.6515        | 4.84  | 3400 | 1.5904          | 0.1925 |
| 1.6003        | 4.99  | 3500 | 1.5899          | 0.1975 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3