|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- wikiann |
|
metrics: |
|
- f1 |
|
base_model: xlm-roberta-base |
|
model-index: |
|
- name: xlm-roberta-base-finetuned-wikiann-hi |
|
results: |
|
- task: |
|
type: token-classification |
|
name: Token Classification |
|
dataset: |
|
name: wikiann |
|
type: wikiann |
|
args: hi |
|
metrics: |
|
- type: f1 |
|
value: 1.0 |
|
name: F1 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# xlm-roberta-base-finetuned-wikiann-hi |
|
|
|
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the wikiann dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3097 |
|
- F1: 1.0 |
|
|
|
## 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: 24 |
|
- eval_batch_size: 24 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:---:| |
|
| 0.5689 | 1.0 | 209 | 0.3179 | 1.0 | |
|
| 0.2718 | 2.0 | 418 | 0.2733 | 1.0 | |
|
| 0.19 | 3.0 | 627 | 0.2560 | 1.0 | |
|
| 0.142 | 4.0 | 836 | 0.2736 | 1.0 | |
|
| 0.0967 | 5.0 | 1045 | 0.2686 | 1.0 | |
|
| 0.0668 | 6.0 | 1254 | 0.2966 | 1.0 | |
|
| 0.052 | 7.0 | 1463 | 0.3194 | 1.0 | |
|
| 0.0369 | 8.0 | 1672 | 0.3034 | 1.0 | |
|
| 0.0236 | 9.0 | 1881 | 0.3174 | 1.0 | |
|
| 0.0135 | 10.0 | 2090 | 0.3097 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.20.1 |
|
- Pytorch 1.12.0+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
