metadata
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_sa_GLUE_Experiment_mrpc_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
config: mrpc
split: validation
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.6911764705882353
- name: F1
type: f1
value: 0.7947882736156351
mobilebert_sa_GLUE_Experiment_mrpc_256
This model is a fine-tuned version of google/mobilebert-uncased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.6111
- Accuracy: 0.6912
- F1: 0.7948
- Combined Score: 0.7430
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 | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.6431 | 1.0 | 29 | 0.6261 | 0.6838 | 0.8122 | 0.7480 |
| 0.6296 | 2.0 | 58 | 0.6235 | 0.6838 | 0.8122 | 0.7480 |
| 0.6306 | 3.0 | 87 | 0.6237 | 0.6838 | 0.8122 | 0.7480 |
| 0.6297 | 4.0 | 116 | 0.6238 | 0.6838 | 0.8122 | 0.7480 |
| 0.6276 | 5.0 | 145 | 0.6207 | 0.6838 | 0.8122 | 0.7480 |
| 0.6197 | 6.0 | 174 | 0.6213 | 0.6838 | 0.8122 | 0.7480 |
| 0.6065 | 7.0 | 203 | 0.6284 | 0.6912 | 0.8043 | 0.7478 |
| 0.5258 | 8.0 | 232 | 0.6111 | 0.6912 | 0.7948 | 0.7430 |
| 0.4596 | 9.0 | 261 | 0.6506 | 0.7034 | 0.8052 | 0.7543 |
| 0.3953 | 10.0 | 290 | 0.7271 | 0.7034 | 0.7932 | 0.7483 |
| 0.3426 | 11.0 | 319 | 0.9509 | 0.6740 | 0.7542 | 0.7141 |
| 0.2821 | 12.0 | 348 | 1.0021 | 0.6863 | 0.7808 | 0.7335 |
| 0.2177 | 13.0 | 377 | 1.0359 | 0.6691 | 0.7676 | 0.7184 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2