---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: medlid-identify
  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. -->

# medlid-identify

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1708
- Precision: 0.3912
- Recall: 0.4603
- F1: 0.4229
- Accuracy: 0.9463

## 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: 81
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 381  | 0.1567          | 0.2689    | 0.3180 | 0.2914 | 0.9377   |
| 0.1618        | 2.0   | 762  | 0.1399          | 0.4016    | 0.3847 | 0.3930 | 0.9492   |
| 0.0978        | 3.0   | 1143 | 0.1505          | 0.3773    | 0.4239 | 0.3993 | 0.9468   |
| 0.0636        | 4.0   | 1524 | 0.1708          | 0.3912    | 0.4603 | 0.4229 | 0.9463   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.11.0
- Datasets 2.13.1
- Tokenizers 0.13.3