|
--- |
|
language: |
|
- en |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: hBERTv1_new_pretrain_w_init_48_sst2 |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE SST2 |
|
type: glue |
|
config: sst2 |
|
split: validation |
|
args: sst2 |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8176605504587156 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# hBERTv1_new_pretrain_w_init_48_sst2 |
|
|
|
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE SST2 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4260 |
|
- Accuracy: 0.8177 |
|
|
|
## 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: 4e-05 |
|
- train_batch_size: 128 |
|
- eval_batch_size: 128 |
|
- seed: 10 |
|
- distributed_type: multi-GPU |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.5336 | 1.0 | 527 | 0.4260 | 0.8177 | |
|
| 0.2532 | 2.0 | 1054 | 0.5554 | 0.8211 | |
|
| 0.1845 | 3.0 | 1581 | 0.5318 | 0.8108 | |
|
| 0.1484 | 4.0 | 2108 | 0.6237 | 0.8108 | |
|
| 0.1195 | 5.0 | 2635 | 0.5310 | 0.8096 | |
|
| 0.1 | 6.0 | 3162 | 0.7588 | 0.8028 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.29.2 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
