---
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: 0.36904761904761907
    - name: Recall
      type: recall
      value: 0.11492122335495829
    - name: F1
      type: f1
      value: 0.1752650176678445
    - name: Accuracy
      type: accuracy
      value: 0.9319911088313243
---

<!-- 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: 0.3070
- Precision: 0.3690
- Recall: 0.1149
- F1: 0.1753
- Accuracy: 0.9320

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 213  | 0.4153          | 0.0       | 0.0    | 0.0    | 0.9256   |
| No log        | 2.0   | 426  | 0.3484          | 0.0       | 0.0    | 0.0    | 0.9256   |
| 0.6399        | 3.0   | 639  | 0.3303          | 0.2222    | 0.0037 | 0.0073 | 0.9256   |
| 0.6399        | 4.0   | 852  | 0.3233          | 0.2179    | 0.0158 | 0.0294 | 0.9269   |
| 0.2004        | 5.0   | 1065 | 0.3164          | 0.3152    | 0.0482 | 0.0836 | 0.9286   |
| 0.2004        | 6.0   | 1278 | 0.3148          | 0.3421    | 0.0723 | 0.1194 | 0.9299   |
| 0.2004        | 7.0   | 1491 | 0.3100          | 0.3653    | 0.0918 | 0.1467 | 0.9309   |
| 0.1861        | 8.0   | 1704 | 0.3083          | 0.3522    | 0.0982 | 0.1536 | 0.9312   |
| 0.1861        | 9.0   | 1917 | 0.3057          | 0.3663    | 0.1168 | 0.1771 | 0.9320   |
| 0.1782        | 10.0  | 2130 | 0.3070          | 0.3690    | 0.1149 | 0.1753 | 0.9320   |


### Framework versions

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