pytorch tensorboard distilbert text-classification transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- f1
model-index:
- name: distil_bert_uncased-finetuned-relations
  results: []
---

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# 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: 0.4191
- Accuracy: 0.8866
- Prec: 0.8771
- Recall: 0.8866
- F1: 0.8808

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|
| 1.1823        | 1.0   | 232  | 0.5940          | 0.8413   | 0.8273 | 0.8413 | 0.8224 |
| 0.4591        | 2.0   | 464  | 0.4600          | 0.8607   | 0.8539 | 0.8607 | 0.8555 |
| 0.3106        | 3.0   | 696  | 0.4160          | 0.8812   | 0.8763 | 0.8812 | 0.8785 |
| 0.246         | 4.0   | 928  | 0.4113          | 0.8834   | 0.8766 | 0.8834 | 0.8796 |
| 0.2013        | 5.0   | 1160 | 0.4191          | 0.8866   | 0.8771 | 0.8866 | 0.8808 |


### Framework versions

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