metadata
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
name: F1
xlm-roberta-base-finetuned-wikiann-hi
This model is a fine-tuned version of 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