File size: 3,178 Bytes
da74cb3 4547ead da74cb3 4547ead da74cb3 4547ead da74cb3 4547ead da74cb3 4547ead da74cb3 |
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 93 94 95 96 97 98 99 100 |
---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: mobilebert_sa_GLUE_Experiment_logit_kd_pretrain_sst2
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: 0.926605504587156
---
<!-- 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_sa_GLUE_Experiment_logit_kd_pretrain_sst2
This model is a fine-tuned version of [gokuls/mobilebert_sa_pre-training-complete](https://huggingface.co/gokuls/mobilebert_sa_pre-training-complete) on the GLUE SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2364
- Accuracy: 0.9266
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4176 | 1.0 | 527 | 0.2978 | 0.9197 |
| 0.1807 | 2.0 | 1054 | 0.2951 | 0.9174 |
| 0.1163 | 3.0 | 1581 | 0.2749 | 0.9186 |
| 0.0862 | 4.0 | 2108 | 0.2988 | 0.9083 |
| 0.0695 | 5.0 | 2635 | 0.2760 | 0.9174 |
| 0.0598 | 6.0 | 3162 | 0.2695 | 0.9151 |
| 0.0525 | 7.0 | 3689 | 0.2723 | 0.9255 |
| 0.0464 | 8.0 | 4216 | 0.2430 | 0.9243 |
| 0.0422 | 9.0 | 4743 | 0.2814 | 0.9243 |
| 0.0395 | 10.0 | 5270 | 0.2464 | 0.9163 |
| 0.0357 | 11.0 | 5797 | 0.2390 | 0.9197 |
| 0.0341 | 12.0 | 6324 | 0.2713 | 0.9197 |
| 0.0328 | 13.0 | 6851 | 0.2685 | 0.9220 |
| 0.0315 | 14.0 | 7378 | 0.2585 | 0.9186 |
| 0.0296 | 15.0 | 7905 | 0.2367 | 0.9220 |
| 0.0283 | 16.0 | 8432 | 0.2560 | 0.9186 |
| 0.0277 | 17.0 | 8959 | 0.2635 | 0.9174 |
| 0.0269 | 18.0 | 9486 | 0.2364 | 0.9266 |
| 0.026 | 19.0 | 10013 | 0.2749 | 0.9209 |
| 0.0252 | 20.0 | 10540 | 0.2507 | 0.9174 |
| 0.0248 | 21.0 | 11067 | 0.2769 | 0.9163 |
| 0.0248 | 22.0 | 11594 | 0.2543 | 0.9220 |
| 0.024 | 23.0 | 12121 | 0.2677 | 0.9209 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
|