metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: funnel-transformer-xlarge_ner_wikiann
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
args: en
metrics:
- name: Precision
type: precision
value: 0.8522084990579862
- name: Recall
type: recall
value: 0.8633535981903011
- name: F1
type: f1
value: 0.8577448467184043
- name: Accuracy
type: accuracy
value: 0.935805105791199
funnel-transformer-xlarge_ner_wikiann
This model is a fine-tuned version of funnel-transformer/xlarge on the wikiann dataset. It achieves the following results on the evaluation set:
- Loss: 0.4023
- Precision: 0.8522
- Recall: 0.8634
- F1: 0.8577
- Accuracy: 0.9358
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.3193 | 1.0 | 5000 | 0.3116 | 0.8239 | 0.8296 | 0.8267 | 0.9260 |
| 0.2836 | 2.0 | 10000 | 0.2846 | 0.8446 | 0.8498 | 0.8472 | 0.9325 |
| 0.2237 | 3.0 | 15000 | 0.3258 | 0.8427 | 0.8542 | 0.8484 | 0.9332 |
| 0.1303 | 4.0 | 20000 | 0.3801 | 0.8531 | 0.8634 | 0.8582 | 0.9362 |
| 0.0867 | 5.0 | 25000 | 0.4023 | 0.8522 | 0.8634 | 0.8577 | 0.9358 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1