File size: 2,892 Bytes
d88410b 453db45 d88410b 453db45 d88410b 453db45 d88410b 453db45 d88410b 453db45 d88410b |
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
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv1_new_pretrain_w_init_48_ver2_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
config: stsb
split: validation
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.12474663100095418
---
<!-- 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_ver2_stsb
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 STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2509
- Pearson: 0.1285
- Spearmanr: 0.1247
- Combined Score: 0.1266
## 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: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.3716 | 1.0 | 90 | 2.4198 | 0.1235 | 0.0756 | 0.0995 |
| 2.1648 | 2.0 | 180 | 2.4218 | 0.0592 | 0.0606 | 0.0599 |
| 2.1915 | 3.0 | 270 | 2.5305 | 0.1143 | 0.0959 | 0.1051 |
| 2.1855 | 4.0 | 360 | 2.4912 | 0.1118 | 0.0969 | 0.1043 |
| 2.1858 | 5.0 | 450 | 2.3539 | 0.1130 | 0.1043 | 0.1087 |
| 2.1818 | 6.0 | 540 | 2.2509 | 0.1285 | 0.1247 | 0.1266 |
| 2.2562 | 7.0 | 630 | 2.3302 | 0.1043 | 0.0974 | 0.1009 |
| 2.2299 | 8.0 | 720 | 2.3749 | 0.1984 | 0.1422 | 0.1703 |
| 2.0676 | 9.0 | 810 | 2.3883 | 0.1300 | 0.1329 | 0.1314 |
| 1.926 | 10.0 | 900 | 2.5884 | 0.1259 | 0.1233 | 0.1246 |
| 1.7701 | 11.0 | 990 | 2.3776 | 0.1911 | 0.2059 | 0.1985 |
### Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
|