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---
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
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