language: | |
- en | |
license: apache-2.0 | |
tags: | |
- generated_from_trainer | |
datasets: | |
- glue | |
metrics: | |
- accuracy | |
model-index: | |
- name: qnli | |
results: | |
- task: | |
name: Text Classification | |
type: text-classification | |
dataset: | |
name: GLUE QNLI | |
type: glue | |
args: qnli | |
metrics: | |
- name: Accuracy | |
type: accuracy | |
value: 0.9068277503203368 | |
<!-- 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. --> | |
# qnli | |
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE QNLI dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.3731 | |
- Accuracy: 0.9068 | |
## 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: 1e-05 | |
- train_batch_size: 32 | |
- eval_batch_size: 8 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 10.0 | |
### Training results | |
### Framework versions | |
- Transformers 4.20.0.dev0 | |
- Pytorch 1.11.0 | |
- Datasets 2.2.2 | |
- Tokenizers 0.12.1 | |