metadata
license: apache-2.0
base_model: michiyasunaga/BioLinkBERT-large
tags:
- generated_from_trainer
datasets:
- scicite
metrics:
- accuracy
model-index:
- name: cite_classification_model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: scicite
type: scicite
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.925764192139738
cite_classification_model
This model is a fine-tuned version of michiyasunaga/BioLinkBERT-large on the scicite dataset. It achieves the following results on the evaluation set:
- Loss: 0.4804
- Accuracy: 0.9258
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2679 | 1.0 | 513 | 0.1976 | 0.9258 |
| 0.1903 | 2.0 | 1026 | 0.2146 | 0.9225 |
| 0.1474 | 3.0 | 1539 | 0.2356 | 0.9225 |
| 0.1105 | 4.0 | 2052 | 0.3363 | 0.9279 |
| 0.0785 | 5.0 | 2565 | 0.3935 | 0.9225 |
| 0.0498 | 6.0 | 3078 | 0.4296 | 0.9236 |
| 0.0293 | 7.0 | 3591 | 0.4774 | 0.9203 |
| 0.0186 | 8.0 | 4104 | 0.4804 | 0.9258 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0