---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: macbert-finetuned-ner-drugname
  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. -->

# macbert-finetuned-ner-drugname

This model is a fine-tuned version of [shibing624/macbert4csc-base-chinese](https://huggingface.co/shibing624/macbert4csc-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0195
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9971

## 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: 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: 8.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.0083        | 1.0   | 15362  | 0.0108          | 0.0       | 0.0    | 0.0 | 0.9964   |
| 0.0053        | 2.0   | 30724  | 0.0116          | 0.0       | 0.0    | 0.0 | 0.9963   |
| 0.0037        | 3.0   | 46086  | 0.0091          | 0.0       | 0.0    | 0.0 | 0.9977   |
| 0.0022        | 4.0   | 61448  | 0.0112          | 0.0       | 0.0    | 0.0 | 0.9975   |
| 0.0017        | 5.0   | 76810  | 0.0150          | 0.0       | 0.0    | 0.0 | 0.9970   |
| 0.0008        | 6.0   | 92172  | 0.0175          | 0.0       | 0.0    | 0.0 | 0.9971   |
| 0.0005        | 7.0   | 107534 | 0.0172          | 0.0       | 0.0    | 0.0 | 0.9971   |
| 0.0002        | 8.0   | 122896 | 0.0195          | 0.0       | 0.0    | 0.0 | 0.9971   |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.17.0
- Tokenizers 0.10.3