---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert_base_data_wnut_17
  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. -->

# distilbert_base_data_wnut_17

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2833
- Precision: 0.5246
- Recall: 0.3855
- F1: 0.4444
- Accuracy: 0.9461

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 213  | 0.2740          | 0.6152    | 0.2919 | 0.3960 | 0.9404   |
| No log        | 2.0   | 426  | 0.2568          | 0.5997    | 0.3679 | 0.4561 | 0.9450   |
| 0.1764        | 3.0   | 639  | 0.2844          | 0.6269    | 0.3457 | 0.4456 | 0.9464   |
| 0.1764        | 4.0   | 852  | 0.2963          | 0.5564    | 0.3522 | 0.4313 | 0.9459   |
| 0.0526        | 5.0   | 1065 | 0.2833          | 0.5246    | 0.3855 | 0.4444 | 0.9461   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1