|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: mobilebert_add_GLUE_Experiment_logit_kd_wnli |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE WNLI |
|
type: glue |
|
config: wnli |
|
split: validation |
|
args: wnli |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.5633802816901409 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# mobilebert_add_GLUE_Experiment_logit_kd_wnli |
|
|
|
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE WNLI dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3448 |
|
- Accuracy: 0.5634 |
|
|
|
## 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: 5e-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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.3478 | 1.0 | 5 | 0.3460 | 0.5634 | |
|
| 0.3477 | 2.0 | 10 | 0.3480 | 0.4366 | |
|
| 0.3466 | 3.0 | 15 | 0.3459 | 0.5634 | |
|
| 0.3466 | 4.0 | 20 | 0.3448 | 0.5634 | |
|
| 0.3468 | 5.0 | 25 | 0.3451 | 0.5634 | |
|
| 0.3467 | 6.0 | 30 | 0.3461 | 0.5634 | |
|
| 0.3465 | 7.0 | 35 | 0.3465 | 0.5634 | |
|
| 0.3466 | 8.0 | 40 | 0.3466 | 0.5634 | |
|
| 0.3468 | 9.0 | 45 | 0.3457 | 0.5634 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.9.0 |
|
- Tokenizers 0.13.2 |
|
|
