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-smallmol-roles-v2
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: source_data_nlp
type: source_data_nlp
args: SMALL_MOL_ROLES
metrics:
- type: precision
value: 0.9628394473558838
name: Precision
- type: recall
value: 0.9716346153846154
name: Recall
- type: f1
value: 0.9672170375687963
name: F1
sd-smallmol-roles-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: 0.0015
- Accuracy Score: 0.9995
- Precision: 0.9628
- Recall: 0.9716
- F1: 0.9672
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 |
|---|---|---|---|---|---|---|---|
| 0.0013 | 1.0 | 1569 | 0.0015 | 0.9995 | 0.9628 | 0.9716 | 0.9672 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0a0+bfe5ad2
- Datasets 1.17.0
- Tokenizers 0.12.1