---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_token_classification_18_techs
  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_token_classification_18_techs

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0228
- Precision: 0.8769
- Recall: 0.9215
- F1: 0.8987
- Accuracy: 0.9927

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6           | 1.0   | 1907  | 0.4260          | 0.3545    | 0.1303 | 0.1906 | 0.8856   |
| 0.4035        | 2.0   | 3814  | 0.2568          | 0.4196    | 0.2961 | 0.3472 | 0.9224   |
| 0.2808        | 3.0   | 5721  | 0.1464          | 0.5921    | 0.5058 | 0.5456 | 0.9568   |
| 0.1648        | 4.0   | 7628  | 0.0952          | 0.6679    | 0.6614 | 0.6646 | 0.9717   |
| 0.1138        | 5.0   | 9535  | 0.0708          | 0.7138    | 0.7422 | 0.7277 | 0.9781   |
| 0.0899        | 6.0   | 11442 | 0.0516          | 0.7779    | 0.7950 | 0.7863 | 0.9840   |
| 0.0609        | 7.0   | 13349 | 0.0357          | 0.8352    | 0.8496 | 0.8423 | 0.9888   |
| 0.0503        | 8.0   | 15256 | 0.0269          | 0.8677    | 0.9010 | 0.8841 | 0.9915   |
| 0.0376        | 9.0   | 17163 | 0.0248          | 0.8700    | 0.9155 | 0.8921 | 0.9920   |
| 0.0331        | 10.0  | 19070 | 0.0228          | 0.8769    | 0.9215 | 0.8987 | 0.9927   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3