---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- trl
- sft
- generated_from_trainer
datasets:
- wnut_17
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-wnut_17-full
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: wnut_17
      type: wnut_17
      config: wnut_17
      split: test
      args: wnut_17
    metrics:
    - name: Precision
      type: precision
      value: 0.6038781163434903
    - name: Recall
      type: recall
      value: 0.4040778498609824
    - name: F1
      type: f1
      value: 0.484175458078845
    - name: Accuracy
      type: accuracy
      value: 0.9478859390363815
---

<!-- 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-uncased-wnut_17-full

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the wnut_17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3599
- Precision: 0.6039
- Recall: 0.4041
- F1: 0.4842
- Accuracy: 0.9479

## 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: 5e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 213  | 0.2609          | 0.5911    | 0.3309 | 0.4242 | 0.9420   |
| No log        | 2.0   | 426  | 0.2808          | 0.5679    | 0.3373 | 0.4233 | 0.9447   |
| 0.133         | 3.0   | 639  | 0.3328          | 0.6591    | 0.3244 | 0.4348 | 0.9461   |
| 0.133         | 4.0   | 852  | 0.3302          | 0.5976    | 0.3689 | 0.4562 | 0.9465   |
| 0.0224        | 5.0   | 1065 | 0.3142          | 0.4955    | 0.4041 | 0.4451 | 0.9445   |
| 0.0224        | 6.0   | 1278 | 0.3599          | 0.6039    | 0.4041 | 0.4842 | 0.9479   |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1