|
---
|
|
license: apache-2.0
|
|
base_model: distilbert-base-uncased
|
|
tags:
|
|
- generated_from_trainer
|
|
metrics:
|
|
- precision
|
|
- recall
|
|
- f1
|
|
- accuracy
|
|
model-index:
|
|
- name: distilbert-base-uncased-finetuned-ner
|
|
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. -->
|
|
|
|
# distilbert-base-uncased-finetuned-ner
|
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.0619
|
|
- Precision: 0.9247
|
|
- Recall: 0.9346
|
|
- F1: 0.9296
|
|
- Accuracy: 0.9832
|
|
|
|
## 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: 3
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
|
| 0.2478 | 1.0 | 878 | 0.0690 | 0.9086 | 0.9195 | 0.9140 | 0.9804 |
|
|
| 0.0515 | 2.0 | 1756 | 0.0597 | 0.9229 | 0.9327 | 0.9278 | 0.9828 |
|
|
| 0.0305 | 3.0 | 2634 | 0.0619 | 0.9247 | 0.9346 | 0.9296 | 0.9832 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.39.3
|
|
- Pytorch 2.2.0+cu118
|
|
- Datasets 2.19.1
|
|
- Tokenizers 0.15.2
|
|
|
