---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_BIOMAT_NER_1000
  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_BIOMAT_NER_1000

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3920
- Precision: 0.9495
- Recall: 0.9444
- F1: 0.9470
- Accuracy: 0.9380

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 211  | 0.2669          | 0.9407    | 0.9352 | 0.9380 | 0.9275   |
| No log        | 2.0   | 422  | 0.2809          | 0.9457    | 0.9432 | 0.9444 | 0.9343   |
| 0.2064        | 3.0   | 633  | 0.3114          | 0.9472    | 0.9454 | 0.9463 | 0.9353   |
| 0.2064        | 4.0   | 844  | 0.3323          | 0.9491    | 0.9422 | 0.9456 | 0.9358   |
| 0.0481        | 5.0   | 1055 | 0.3478          | 0.9493    | 0.9441 | 0.9467 | 0.9382   |
| 0.0481        | 6.0   | 1266 | 0.3731          | 0.9486    | 0.9438 | 0.9462 | 0.9374   |
| 0.0481        | 7.0   | 1477 | 0.3723          | 0.9491    | 0.9445 | 0.9468 | 0.9379   |
| 0.0201        | 8.0   | 1688 | 0.3830          | 0.9489    | 0.9443 | 0.9466 | 0.9369   |
| 0.0201        | 9.0   | 1899 | 0.3873          | 0.9503    | 0.9448 | 0.9475 | 0.9378   |
| 0.0106        | 10.0  | 2110 | 0.3920          | 0.9495    | 0.9444 | 0.9470 | 0.9380   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1