|
--- |
|
language: |
|
- en |
|
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: hBERTv1_new_pretrain_w_init_48_ver2_rte |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE RTE |
|
type: glue |
|
config: rte |
|
split: validation |
|
args: rte |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.5270758122743683 |
|
--- |
|
|
|
<!-- 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_ver2_rte |
|
|
|
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 RTE dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6919 |
|
- Accuracy: 0.5271 |
|
|
|
## 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: 64 |
|
- eval_batch_size: 64 |
|
- seed: 10 |
|
- distributed_type: multi-GPU |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.7175 | 1.0 | 39 | 0.6919 | 0.5271 | |
|
| 0.7099 | 2.0 | 78 | 0.7006 | 0.4729 | |
|
| 0.7111 | 3.0 | 117 | 0.6927 | 0.5271 | |
|
| 0.7011 | 4.0 | 156 | 0.6976 | 0.4729 | |
|
| 0.7021 | 5.0 | 195 | 0.6955 | 0.4729 | |
|
| 0.6986 | 6.0 | 234 | 0.7078 | 0.4729 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
