metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- source_data_nlp
metrics:
- precision
- recall
- f1
base_model: michiyasunaga/BioLinkBERT-large
model-index:
- name: sd-panelization-v2
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: source_data_nlp
type: source_data_nlp
args: PANELIZATION
metrics:
- type: precision
value: 0.9134245120169964
name: Precision
- type: recall
value: 0.9494824016563147
name: Recall
- type: f1
value: 0.9311044937736871
name: F1
sd-panelization-v2
This model is a fine-tuned version of michiyasunaga/BioLinkBERT-large on the source_data_nlp dataset. It achieves the following results on the evaluation set:
- Loss: 0.0050
- Accuracy Score: 0.9982
- Precision: 0.9134
- Recall: 0.9495
- F1: 0.9311
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: 32
- eval_batch_size: 256
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0048 | 1.0 | 431 | 0.0050 | 0.9982 | 0.9134 | 0.9495 | 0.9311 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0a0+bfe5ad2
- Datasets 1.17.0
- Tokenizers 0.12.1