|
--- |
|
license: apache-2.0 |
|
base_model: bert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- arxiv_dataset |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: baseline_BERT_50K_steps |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: arxiv_dataset |
|
type: arxiv_dataset |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9936787420400056 |
|
- name: Precision |
|
type: precision |
|
value: 0.7967781908302355 |
|
- name: Recall |
|
type: recall |
|
value: 0.4734468476760239 |
|
- name: F1 |
|
type: f1 |
|
value: 0.5939610876970152 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# baseline_BERT_50K_steps |
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the arxiv_dataset dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0192 |
|
- Accuracy: 0.9937 |
|
- Precision: 0.7968 |
|
- Recall: 0.4734 |
|
- F1: 0.5940 |
|
- Hamming: 0.0063 |
|
|
|
## 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: 6 |
|
- eval_batch_size: 6 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- training_steps: 50000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Hamming | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
|
| 0.0343 | 0.03 | 10000 | 0.0315 | 0.9912 | 0.7679 | 0.1370 | 0.2326 | 0.0088 | |
|
| 0.0244 | 0.06 | 20000 | 0.0234 | 0.9925 | 0.7813 | 0.3262 | 0.4602 | 0.0075 | |
|
| 0.0219 | 0.09 | 30000 | 0.0210 | 0.9931 | 0.7572 | 0.4320 | 0.5502 | 0.0069 | |
|
| 0.0204 | 0.12 | 40000 | 0.0197 | 0.9935 | 0.7738 | 0.4711 | 0.5857 | 0.0065 | |
|
| 0.0197 | 0.15 | 50000 | 0.0192 | 0.9937 | 0.7968 | 0.4734 | 0.5940 | 0.0063 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
