---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: clarifier-good-name-xlm-roberta
  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. -->

# clarifier-good-name-xlm-roberta

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3007
- F1: 0.8746

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2794        | 1.0   | 553  | 0.2373          | 0.8460 |
| 0.208         | 2.0   | 1106 | 0.2176          | 0.8585 |
| 0.1915        | 3.0   | 1659 | 0.2057          | 0.8542 |
| 0.1662        | 4.0   | 2212 | 0.2216          | 0.8635 |
| 0.1472        | 5.0   | 2765 | 0.2160          | 0.8709 |
| 0.132         | 6.0   | 3318 | 0.2297          | 0.8703 |
| 0.1255        | 7.0   | 3871 | 0.2617          | 0.8709 |
| 0.1162        | 8.0   | 4424 | 0.2973          | 0.8738 |
| 0.1036        | 9.0   | 4977 | 0.2818          | 0.8713 |
| 0.1           | 10.0  | 5530 | 0.3007          | 0.8746 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.0
- Tokenizers 0.13.3