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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: mobilebert_add_GLUE_Experiment_stsb_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
config: stsb
split: validation
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.02173520720193955
---
<!-- 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_stsb_256
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2965
- Pearson: 0.0399
- Spearmanr: 0.0217
- Combined Score: 0.0308
## 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 | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 4.3289 | 1.0 | 45 | 2.5185 | 0.0152 | 0.0186 | 0.0169 |
| 2.1532 | 2.0 | 90 | 2.5569 | 0.0388 | 0.0235 | 0.0312 |
| 2.1161 | 3.0 | 135 | 2.2965 | 0.0399 | 0.0217 | 0.0308 |
| 2.1083 | 4.0 | 180 | 2.4191 | 0.0409 | 0.0284 | 0.0347 |
| 2.0885 | 5.0 | 225 | 2.5610 | 0.0458 | 0.0382 | 0.0420 |
| 2.0602 | 6.0 | 270 | 2.3788 | 0.0473 | 0.0444 | 0.0458 |
| 2.0283 | 7.0 | 315 | 2.4459 | 0.0571 | 0.0527 | 0.0549 |
| 1.9677 | 8.0 | 360 | 2.4995 | 0.0614 | 0.0604 | 0.0609 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
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