---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_token_classification_14_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_14_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: 0.0225
- Precision: 0.8752
- Recall: 0.9167
- F1: 0.8955
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5777        | 1.0   | 1907  | 0.4271          | 0.3517    | 0.0988 | 0.1543 | 0.8843   |
| 0.3951        | 2.0   | 3814  | 0.2512          | 0.4325    | 0.3259 | 0.3717 | 0.9227   |
| 0.2678        | 3.0   | 5721  | 0.1405          | 0.5783    | 0.5598 | 0.5689 | 0.9580   |
| 0.153         | 4.0   | 7628  | 0.0924          | 0.6640    | 0.6804 | 0.6721 | 0.9725   |
| 0.1129        | 5.0   | 9535  | 0.0717          | 0.7014    | 0.7462 | 0.7231 | 0.9773   |
| 0.0798        | 6.0   | 11442 | 0.0598          | 0.7699    | 0.8102 | 0.7895 | 0.9832   |
| 0.0637        | 7.0   | 13349 | 0.0405          | 0.8221    | 0.8484 | 0.8351 | 0.9883   |
| 0.0483        | 8.0   | 15256 | 0.0307          | 0.8259    | 0.8818 | 0.8529 | 0.9893   |
| 0.0375        | 9.0   | 17163 | 0.0244          | 0.8674    | 0.9123 | 0.8893 | 0.9919   |
| 0.0315        | 10.0  | 19070 | 0.0225          | 0.8752    | 0.9167 | 0.8955 | 0.9927   |


### Framework versions

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