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named-entity-tr
pnr-svc/named-entity-tr
named-entity-tr is a token classification model from pnr-svc. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
tags: - generatedfromtrainer datasets: - ner-tr metrics: - precision - recall - f1 - accuracy model-index: - name: named-entity-tr results: - task: name: Token Classification type: token-classification dataset: name:…
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- electra
- Access
- Public
- Created
- Sep 15, 2022
- Updated
- Sep 15, 2022
- SHA
- e04f47af
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Model card
From the Hugging Face model README
tags:
- generated_from_trainer datasets:
- ner-tr metrics:
- precision
- recall
- f1
- accuracy model-index:
- name: named-entity-tr
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ner-tr
type: ner-tr
config: NERTR
split: train
args: NERTR
metrics:
- name: Precision type: precision value: 0.0
- name: Recall type: recall value: 0.0
- name: F1 type: f1 value: 0.0
- name: Accuracy type: accuracy value: 0.45027322404371584
- task:
name: Token Classification
type: token-classification
dataset:
name: ner-tr
type: ner-tr
config: NERTR
split: train
args: NERTR
metrics:
<!-- 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. -->
named-entity-tr
This model is a fine-tuned version of dbmdz/electra-base-turkish-cased-discriminator on the ner-tr dataset. It achieves the following results on the evaluation set:
- Loss: 2.2782
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.4503
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 9 | 2.7645 | 0.0537 | 0.0777 | 0.0635 | 0.3191 |
| No log | 2.0 | 18 | 2.3464 | 0.0 | 0.0 | 0.0 | 0.4503 |
| No log | 3.0 | 27 | 2.2782 | 0.0 | 0.0 | 0.0 | 0.4503 |
Framework versions
- Transformers 4.22.0
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Token Classification
- Library
- transformers
- Type
- electra
- License
- mit
- Created
- Sep 15, 2022
- Updated
- Sep 15, 2022