|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: mobilebert_add_GLUE_Experiment_sst2_128 |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE SST2 |
|
type: glue |
|
config: sst2 |
|
split: validation |
|
args: sst2 |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.7981651376146789 |
|
--- |
|
|
|
<!-- 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_sst2_128 |
|
|
|
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE SST2 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4543 |
|
- Accuracy: 0.7982 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.6677 | 1.0 | 527 | 0.6771 | 0.5757 | |
|
| 0.5966 | 2.0 | 1054 | 0.7135 | 0.5424 | |
|
| 0.5714 | 3.0 | 1581 | 0.7271 | 0.5550 | |
|
| 0.5573 | 4.0 | 2108 | 0.6892 | 0.5619 | |
|
| 0.501 | 5.0 | 2635 | 0.4546 | 0.7798 | |
|
| 0.2856 | 6.0 | 3162 | 0.4613 | 0.8050 | |
|
| 0.2288 | 7.0 | 3689 | 0.4543 | 0.7982 | |
|
| 0.2027 | 8.0 | 4216 | 0.4662 | 0.7993 | |
|
| 0.1883 | 9.0 | 4743 | 0.5168 | 0.8039 | |
|
| 0.1779 | 10.0 | 5270 | 0.5748 | 0.7856 | |
|
| 0.1691 | 11.0 | 5797 | 0.5196 | 0.8028 | |
|
| 0.1596 | 12.0 | 6324 | 0.5943 | 0.7947 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
