metadata
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv1_new_pretrain_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: 0.5306859205776173
hBERTv1_new_pretrain_rte
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.6896
- Accuracy: 0.5307
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 |
|---|---|---|---|---|
| 0.7407 | 1.0 | 20 | 0.7002 | 0.4729 |
| 0.7061 | 2.0 | 40 | 0.7245 | 0.4729 |
| 0.7102 | 3.0 | 60 | 0.6949 | 0.5271 |
| 0.703 | 4.0 | 80 | 0.6951 | 0.4729 |
| 0.7097 | 5.0 | 100 | 0.6974 | 0.4729 |
| 0.7006 | 6.0 | 120 | 0.7053 | 0.4729 |
| 0.6986 | 7.0 | 140 | 0.6896 | 0.5307 |
| 0.6935 | 8.0 | 160 | 0.7711 | 0.4729 |
| 0.6109 | 9.0 | 180 | 0.8443 | 0.4982 |
| 0.469 | 10.0 | 200 | 1.0369 | 0.5126 |
| 0.3028 | 11.0 | 220 | 1.1621 | 0.5235 |
| 0.2155 | 12.0 | 240 | 1.2096 | 0.5379 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3