metadata
license: cc-by-nc-4.0
base_model: s2w-ai/DarkBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DarkBERT-finetuned-ner
results: []
DarkBERT-finetuned-ner
This model is a fine-tuned version of s2w-ai/DarkBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6416
- Precision: 0.4628
- Recall: 0.5470
- F1: 0.5014
- Accuracy: 0.8901
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 111 | 0.3933 | 0.3563 | 0.4337 | 0.3912 | 0.8726 |
| No log | 2.0 | 222 | 0.3491 | 0.4345 | 0.5672 | 0.4921 | 0.8886 |
| No log | 3.0 | 333 | 0.3991 | 0.4284 | 0.5405 | 0.4780 | 0.8795 |
| No log | 4.0 | 444 | 0.3969 | 0.4565 | 0.5797 | 0.5108 | 0.8877 |
| 0.2744 | 5.0 | 555 | 0.4276 | 0.4737 | 0.5690 | 0.5170 | 0.8887 |
| 0.2744 | 6.0 | 666 | 0.5237 | 0.4918 | 0.5637 | 0.5253 | 0.8862 |
| 0.2744 | 7.0 | 777 | 0.5472 | 0.4855 | 0.5503 | 0.5159 | 0.8877 |
| 0.2744 | 8.0 | 888 | 0.6319 | 0.4581 | 0.5699 | 0.5079 | 0.8855 |
| 0.2744 | 9.0 | 999 | 0.6511 | 0.4901 | 0.5744 | 0.5289 | 0.8901 |
| 0.0627 | 10.0 | 1110 | 0.6758 | 0.4900 | 0.5681 | 0.5262 | 0.8899 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1