|
--- |
|
license: apache-2.0 |
|
base_model: onlplab/alephbert-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- nemo_corpus |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: aleph_bert-finetuned-ner |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: nemo_corpus |
|
type: nemo_corpus |
|
config: flat_token |
|
split: validation |
|
args: flat_token |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.8333333333333334 |
|
- name: Recall |
|
type: recall |
|
value: 0.8262454434993924 |
|
- name: F1 |
|
type: f1 |
|
value: 0.8297742525930445 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9739268365222564 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# aleph_bert-finetuned-ner |
|
|
|
This model is a fine-tuned version of [onlplab/alephbert-base](https://huggingface.co/onlplab/alephbert-base) on the nemo_corpus dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1408 |
|
- Precision: 0.8333 |
|
- Recall: 0.8262 |
|
- F1: 0.8298 |
|
- Accuracy: 0.9739 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.042 | 1.0 | 618 | 0.1317 | 0.8198 | 0.8068 | 0.8132 | 0.9720 | |
|
| 0.0185 | 2.0 | 1236 | 0.1367 | 0.8224 | 0.8214 | 0.8219 | 0.9714 | |
|
| 0.0185 | 3.0 | 1854 | 0.1408 | 0.8333 | 0.8262 | 0.8298 | 0.9739 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.0.1+cpu |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
