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library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_km_5_v2_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.4647300879795164
---
<!-- 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_km_5_v2_stsb
This model is a fine-tuned version of [Hartunka/bert_base_km_5_v2](https://huggingface.co/Hartunka/bert_base_km_5_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8177
- Pearson: 0.4729
- Spearmanr: 0.4647
- Combined Score: 0.4688
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.6459 | 1.0 | 23 | 2.4966 | 0.1835 | 0.1715 | 0.1775 |
| 1.8235 | 2.0 | 46 | 2.2914 | 0.3594 | 0.3550 | 0.3572 |
| 1.4306 | 3.0 | 69 | 2.0514 | 0.4242 | 0.4267 | 0.4254 |
| 1.0154 | 4.0 | 92 | 1.8177 | 0.4729 | 0.4647 | 0.4688 |
| 0.6595 | 5.0 | 115 | 2.1356 | 0.4311 | 0.4288 | 0.4299 |
| 0.5214 | 6.0 | 138 | 2.0065 | 0.4628 | 0.4615 | 0.4621 |
| 0.3787 | 7.0 | 161 | 2.2221 | 0.4495 | 0.4408 | 0.4451 |
| 0.3169 | 8.0 | 184 | 2.1129 | 0.4652 | 0.4569 | 0.4611 |
| 0.2679 | 9.0 | 207 | 2.1071 | 0.4559 | 0.4422 | 0.4491 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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