File size: 2,580 Bytes
08625a9 f49c88e 08625a9 f49c88e 08625a9 f49c88e 08625a9 f49c88e 08625a9 f49c88e 08625a9 f49c88e 08625a9 |
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 |
---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_new_pretrain_w_init_48_qqp
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: 0.8430373485035865
- name: F1
type: f1
value: 0.7845307619176966
---
<!-- 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. -->
# hBERTv1_new_pretrain_w_init_48_qqp
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3476
- Accuracy: 0.8430
- F1: 0.7845
- Combined Score: 0.8138
## 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: 4e-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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4637 | 1.0 | 2843 | 0.3907 | 0.8136 | 0.7636 | 0.7886 |
| 0.363 | 2.0 | 5686 | 0.3536 | 0.8338 | 0.7900 | 0.8119 |
| 0.3211 | 3.0 | 8529 | 0.3476 | 0.8430 | 0.7845 | 0.8138 |
| 0.2906 | 4.0 | 11372 | 0.3539 | 0.8531 | 0.8059 | 0.8295 |
| 0.2603 | 5.0 | 14215 | 0.3531 | 0.8531 | 0.8017 | 0.8274 |
| 0.2373 | 6.0 | 17058 | 0.3716 | 0.8561 | 0.8089 | 0.8325 |
| 0.2175 | 7.0 | 19901 | 0.3553 | 0.8565 | 0.8123 | 0.8344 |
| 0.1957 | 8.0 | 22744 | 0.3726 | 0.8551 | 0.8099 | 0.8325 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
|