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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_lda_100_v1_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.5325439607950028
---
<!-- 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_base_lda_100_v1_stsb
This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_100_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6844
- Pearson: 0.5330
- Spearmanr: 0.5325
- Combined Score: 0.5328
## 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 | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.7331 | 1.0 | 23 | 2.6189 | 0.0643 | 0.0760 | 0.0701 |
| 1.9804 | 2.0 | 46 | 2.0897 | 0.2818 | 0.2688 | 0.2753 |
| 1.7486 | 3.0 | 69 | 1.9471 | 0.4158 | 0.4153 | 0.4155 |
| 1.2963 | 4.0 | 92 | 2.3058 | 0.4520 | 0.4674 | 0.4597 |
| 1.0162 | 5.0 | 115 | 1.8442 | 0.4887 | 0.4888 | 0.4888 |
| 0.8446 | 6.0 | 138 | 1.7664 | 0.5228 | 0.5290 | 0.5259 |
| 0.6767 | 7.0 | 161 | 1.7574 | 0.5152 | 0.5185 | 0.5168 |
| 0.5349 | 8.0 | 184 | 1.6844 | 0.5330 | 0.5325 | 0.5328 |
| 0.4606 | 9.0 | 207 | 1.9862 | 0.5039 | 0.5084 | 0.5062 |
| 0.3951 | 10.0 | 230 | 1.8024 | 0.5266 | 0.5275 | 0.5270 |
| 0.3624 | 11.0 | 253 | 2.0157 | 0.5342 | 0.5423 | 0.5382 |
| 0.3087 | 12.0 | 276 | 2.4094 | 0.5227 | 0.5385 | 0.5306 |
| 0.2879 | 13.0 | 299 | 2.0560 | 0.5304 | 0.5350 | 0.5327 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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