|
--- |
|
library_name: transformers |
|
language: |
|
- en |
|
base_model: gokulsrinivasagan/bert_tiny_lda_50_v1_book |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: bert_tiny_lda_50_v1_book_qqp |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE QQP |
|
type: glue |
|
args: qqp |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8727924808310661 |
|
- name: F1 |
|
type: f1 |
|
value: 0.8236584947711297 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# bert_tiny_lda_50_v1_book_qqp |
|
|
|
This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_50_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_50_v1_book) on the GLUE QQP dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3001 |
|
- Accuracy: 0.8728 |
|
- F1: 0.8237 |
|
- Combined Score: 0.8482 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 256 |
|
- eval_batch_size: 256 |
|
- seed: 10 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- num_epochs: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:| |
|
| 0.4008 | 1.0 | 1422 | 0.3670 | 0.8389 | 0.7596 | 0.7993 | |
|
| 0.3043 | 2.0 | 2844 | 0.3162 | 0.8636 | 0.8129 | 0.8383 | |
|
| 0.2505 | 3.0 | 4266 | 0.3001 | 0.8728 | 0.8237 | 0.8482 | |
|
| 0.2074 | 4.0 | 5688 | 0.3213 | 0.8740 | 0.8186 | 0.8463 | |
|
| 0.1699 | 5.0 | 7110 | 0.3346 | 0.8776 | 0.8287 | 0.8531 | |
|
| 0.1392 | 6.0 | 8532 | 0.3586 | 0.8808 | 0.8395 | 0.8602 | |
|
| 0.1151 | 7.0 | 9954 | 0.3763 | 0.8820 | 0.8390 | 0.8605 | |
|
| 0.0954 | 8.0 | 11376 | 0.3984 | 0.8820 | 0.8376 | 0.8598 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.3 |
|
- Pytorch 2.2.1+cu118 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.20.3 |
|
|
