metadata
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv1_no_pretrain_qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
config: qnli
split: validation
args: qnli
metrics:
- name: Accuracy
type: accuracy
value: 0.5053999633900788
hBERTv1_no_pretrain_qnli
This model is a fine-tuned version of on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6931
- Accuracy: 0.5054
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: 96
- eval_batch_size: 96
- 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 |
|---|---|---|---|---|
| 0.7059 | 1.0 | 1092 | 0.7004 | 0.5054 |
| 0.6948 | 2.0 | 2184 | 0.6938 | 0.4946 |
| 0.6939 | 3.0 | 3276 | 0.6932 | 0.5054 |
| 0.6936 | 4.0 | 4368 | 0.6931 | 0.5054 |
| 0.6934 | 5.0 | 5460 | 0.6931 | 0.5054 |
| 0.6936 | 6.0 | 6552 | 0.6931 | 0.5054 |
| 0.6933 | 7.0 | 7644 | 0.6931 | 0.5054 |
| 0.6933 | 8.0 | 8736 | 0.6931 | 0.5054 |
| 0.6934 | 9.0 | 9828 | 0.6934 | 0.5054 |
| 0.6933 | 10.0 | 10920 | 0.6931 | 0.5054 |
| 0.6932 | 11.0 | 12012 | 0.6933 | 0.4946 |
| 0.6932 | 12.0 | 13104 | 0.6931 | 0.5054 |
| 0.6933 | 13.0 | 14196 | 0.6931 | 0.5054 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3