File size: 2,622 Bytes
eb8e679 441bdde eb8e679 441bdde eb8e679 441bdde eb8e679 441bdde eb8e679 441bdde eb8e679 441bdde eb8e679 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_add_GLUE_Experiment_qqp_128
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
config: qqp
split: validation
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.7568142468464012
- name: F1
type: f1
value: 0.6361483235881874
---
<!-- 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_qqp_128
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5071
- Accuracy: 0.7568
- F1: 0.6361
- Combined Score: 0.6965
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6507 | 1.0 | 2843 | 0.6497 | 0.6318 | 0.0 | 0.3159 |
| 0.6311 | 2.0 | 5686 | 0.5445 | 0.7259 | 0.5622 | 0.6441 |
| 0.5153 | 3.0 | 8529 | 0.5153 | 0.7493 | 0.5892 | 0.6693 |
| 0.4912 | 4.0 | 11372 | 0.5071 | 0.7568 | 0.6361 | 0.6965 |
| 0.4805 | 5.0 | 14215 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 6.0 | 17058 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 7.0 | 19901 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 8.0 | 22744 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 9.0 | 25587 | nan | 0.6318 | 0.0 | 0.3159 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
|