|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
base_model: dslim/bert-large-NER |
|
model-index: |
|
- name: bert-finetuned-ner-adam |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# bert-finetuned-ner-adam |
|
|
|
This model is a fine-tuned version of [dslim/bert-large-NER](https://huggingface.co/dslim/bert-large-NER) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: nan |
|
- Precision: 0.8340 |
|
- Recall: 0.8131 |
|
- F1: 0.8234 |
|
- Accuracy: 0.9216 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.1744 | 1.0 | 893 | nan | 0.8276 | 0.8115 | 0.8195 | 0.9205 | |
|
| 0.128 | 2.0 | 1786 | nan | 0.8404 | 0.8256 | 0.8329 | 0.9238 | |
|
| 0.0768 | 3.0 | 2679 | nan | 0.8340 | 0.8131 | 0.8234 | 0.9216 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
