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

# my_awesome_wnut_all_NEG

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0175
- Precision: 0.7955
- Recall: 0.8537
- F1: 0.8235
- Accuracy: 0.9948

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 251  | 0.0170          | 0.8056    | 0.8488 | 0.8266 | 0.9948   |
| 0.0275        | 2.0   | 502  | 0.0166          | 0.7937    | 0.8634 | 0.8271 | 0.9948   |
| 0.0275        | 3.0   | 753  | 0.0169          | 0.7982    | 0.8683 | 0.8318 | 0.9947   |
| 0.0083        | 4.0   | 1004 | 0.0175          | 0.7955    | 0.8537 | 0.8235 | 0.9948   |


### Framework versions

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