File size: 2,844 Bytes
c013239 a1c60a3 c013239 a1c60a3 c013239 a1c60a3 c013239 a1c60a3 c013239 a1c60a3 c013239 6175228 c013239 6175228 c013239 |
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 |
---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_tiny_lda_100_v1_qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8543408360128617
- name: F1
type: f1
value: 0.8063020096700984
---
<!-- 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. -->
# bert_tiny_lda_100_v1_qqp
This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3551
- Accuracy: 0.8543
- F1: 0.8063
- Combined Score: 0.8303
## 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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4874 | 1.0 | 1422 | 0.4274 | 0.7980 | 0.7125 | 0.7553 |
| 0.388 | 2.0 | 2844 | 0.3786 | 0.8224 | 0.7726 | 0.7975 |
| 0.3354 | 3.0 | 4266 | 0.3613 | 0.8372 | 0.7899 | 0.8136 |
| 0.2928 | 4.0 | 5688 | 0.3564 | 0.8447 | 0.7830 | 0.8139 |
| 0.2583 | 5.0 | 7110 | 0.3614 | 0.8509 | 0.7997 | 0.8253 |
| 0.2277 | 6.0 | 8532 | 0.3551 | 0.8543 | 0.8063 | 0.8303 |
| 0.2014 | 7.0 | 9954 | 0.3854 | 0.8552 | 0.8093 | 0.8322 |
| 0.1784 | 8.0 | 11376 | 0.3979 | 0.8545 | 0.8064 | 0.8305 |
| 0.1578 | 9.0 | 12798 | 0.4261 | 0.8558 | 0.8102 | 0.8330 |
| 0.1403 | 10.0 | 14220 | 0.4443 | 0.8588 | 0.8108 | 0.8348 |
| 0.1246 | 11.0 | 15642 | 0.4678 | 0.8567 | 0.8093 | 0.8330 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
|