metadata
license: mit
base_model: numind/NuNER-v1.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nuner-v1_ontonotes5
results: []
nuner-v1_ontonotes5
This model is a fine-tuned version of numind/NuNER-v1.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0728
- Precision: 0.8712
- Recall: 0.9000
- F1: 0.8853
- Accuracy: 0.9811
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: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0781 | 1.0 | 936 | 0.0754 | 0.8392 | 0.8843 | 0.8612 | 0.9778 |
| 0.049 | 2.0 | 1873 | 0.0685 | 0.8597 | 0.8935 | 0.8763 | 0.9794 |
| 0.0357 | 3.0 | 2809 | 0.0714 | 0.8608 | 0.9016 | 0.8807 | 0.9806 |
| 0.027 | 4.0 | 3744 | 0.0728 | 0.8712 | 0.9000 | 0.8853 | 0.9811 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2