---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: sequence-ranker-for-dbpedia-ontology
  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. -->

# test_trainer

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0633
- F1: 0.3413
- Precision: 0.2765
- Recall: 0.4456
- Accuracy: 0.7017

## 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: 1e-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

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
| 0.6981        | 1.0   | 285  | 0.6720          | 0.3035 | 0.2919    | 0.3161 | 0.7484   |
| 0.6726        | 2.0   | 570  | 0.6554          | 0.3547 | 0.2740    | 0.5026 | 0.6828   |
| 0.6402        | 3.0   | 855  | 0.6574          | 0.3609 | 0.2675    | 0.5544 | 0.6595   |
| 0.568         | 4.0   | 1140 | 0.7293          | 0.3620 | 0.3154    | 0.4249 | 0.7403   |
| 0.4926        | 5.0   | 1425 | 0.8515          | 0.3383 | 0.2883    | 0.4093 | 0.7224   |
| 0.4303        | 6.0   | 1710 | 0.9507          | 0.3538 | 0.2813    | 0.4767 | 0.6981   |
| 0.38          | 7.0   | 1995 | 1.0129          | 0.3366 | 0.2685    | 0.4508 | 0.6918   |
| 0.3437        | 8.0   | 2280 | 1.0633          | 0.3413 | 0.2765    | 0.4456 | 0.7017   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2