|
--- |
|
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 |
|
|
