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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wnut_17
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-multilingual-cased-WNUT-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wnut_17
type: wnut_17
config: wnut_17
split: test
args: wnut_17
metrics:
- name: Precision
type: precision
value: 0.5496503496503496
- name: Recall
type: recall
value: 0.36422613531047265
- name: F1
type: f1
value: 0.4381270903010034
- name: Accuracy
type: accuracy
value: 0.9468667179618706
---
<!-- 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. -->
# distilbert-base-multilingual-cased-WNUT-ner
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the wnut_17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3516
- Precision: 0.5497
- Recall: 0.3642
- F1: 0.4381
- Accuracy: 0.9469
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 213 | 0.2727 | 0.6626 | 0.2530 | 0.3662 | 0.9402 |
| No log | 2.0 | 426 | 0.2636 | 0.5895 | 0.2715 | 0.3718 | 0.9429 |
| 0.1729 | 3.0 | 639 | 0.2933 | 0.5931 | 0.3040 | 0.4020 | 0.9447 |
| 0.1729 | 4.0 | 852 | 0.2861 | 0.5437 | 0.3457 | 0.4227 | 0.9453 |
| 0.0503 | 5.0 | 1065 | 0.3270 | 0.5627 | 0.3494 | 0.4311 | 0.9455 |
| 0.0503 | 6.0 | 1278 | 0.3277 | 0.5451 | 0.3531 | 0.4286 | 0.9463 |
| 0.0503 | 7.0 | 1491 | 0.3471 | 0.5828 | 0.3457 | 0.4340 | 0.9467 |
| 0.0231 | 8.0 | 1704 | 0.3594 | 0.5801 | 0.3457 | 0.4332 | 0.9464 |
| 0.0231 | 9.0 | 1917 | 0.3550 | 0.5567 | 0.3503 | 0.4300 | 0.9467 |
| 0.0121 | 10.0 | 2130 | 0.3516 | 0.5497 | 0.3642 | 0.4381 | 0.9469 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
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