---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- f1
model-index:
- name: distil_bert_uncased-finetuned-relations
  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. -->

# distil_bert_uncased-finetuned-relations

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3626
- Accuracy: 0.9082
- Prec: 0.9061
- Recall: 0.9082
- F1: 0.9065

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Prec   | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|
| 0.2981        | 1.0   | 232  | 0.3442          | 0.9039   | 0.9014 | 0.9039 | 0.9018 |
| 0.2037        | 2.0   | 464  | 0.3400          | 0.8996   | 0.8980 | 0.8996 | 0.8974 |
| 0.1499        | 3.0   | 696  | 0.3501          | 0.9017   | 0.8979 | 0.9017 | 0.8980 |
| 0.1043        | 4.0   | 928  | 0.3545          | 0.9028   | 0.8979 | 0.9028 | 0.8994 |
| 0.0803        | 5.0   | 1160 | 0.3626          | 0.9082   | 0.9061 | 0.9082 | 0.9065 |


### Framework versions

- Transformers 4.19.4
- Pytorch 1.13.0.dev20220614
- Datasets 2.2.2
- Tokenizers 0.11.6