---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- wnut_17
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ChatGPT_Project
  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: 0.07692307692307693
    - name: Recall
      type: recall
      value: 0.0009267840593141798
    - name: F1
      type: f1
      value: 0.0018315018315018315
    - name: Accuracy
      type: accuracy
      value: 0.9257929383602633
---

<!-- 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. -->

# ChatGPT_Project

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wnut_17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3261
- Precision: 0.0769
- Recall: 0.0009
- F1: 0.0018
- Accuracy: 0.9258

## 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  | 0.4147          | 0.0       | 0.0    | 0.0    | 0.9256   |
| No log        | 2.0   | 426  | 0.3513          | 0.0       | 0.0    | 0.0    | 0.9256   |
| 0.6236        | 3.0   | 639  | 0.3337          | 0.3333    | 0.0009 | 0.0018 | 0.9257   |
| 0.6236        | 4.0   | 852  | 0.3272          | 0.1111    | 0.0009 | 0.0018 | 0.9258   |
| 0.208         | 5.0   | 1065 | 0.3261          | 0.0769    | 0.0009 | 0.0018 | 0.9258   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0