---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: quote-type-sentence-model
  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. -->

# quote-type-sentence-model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) to perform sentence level classification on 
a news dataset. The following sentence level tags are identified:

```
  'No Quote'
  'Direct Quote'
  'Published Work/Press Report'
  'Indirect Quote'
  'Statement/Public Speech'
  'Background/Narrative'
  'Other'
  'Proposal/Order/Law'
  'Email/Social Media Post'
  'Court Proceeding'
  'Direct Observation'
```

It achieves the following results on the evaluation set:
- Loss: 0.8795
- F1: 0.5407

## 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-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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.19  | 100  | 1.1174          | 0.2831 |
| No log        | 0.38  | 200  | 1.1066          | 0.3356 |
| No log        | 0.57  | 300  | 1.0490          | 0.4126 |
| No log        | 0.76  | 400  | 1.0280          | 0.3778 |
| 1.0973        | 0.95  | 500  | 0.9378          | 0.4492 |
| 1.0973        | 1.14  | 600  | 1.0546          | 0.4650 |
| 1.0973        | 1.33  | 700  | 0.9806          | 0.4619 |
| 1.0973        | 1.52  | 800  | 0.8989          | 0.5176 |
| 1.0973        | 1.7   | 900  | 0.9531          | 0.5078 |
| 0.8155        | 1.89  | 1000 | 0.9482          | 0.4781 |
| 0.8155        | 2.08  | 1100 | 0.8935          | 0.5084 |
| 0.8155        | 2.27  | 1200 | 0.9059          | 0.5236 |
| 0.8155        | 2.46  | 1300 | 0.9483          | 0.5127 |
| 0.8155        | 2.65  | 1400 | 0.8961          | 0.5355 |
| 0.6225        | 2.84  | 1500 | 0.8795          | 0.5407 |


### Framework versions

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