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---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_km_50_v1_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.2801121104631292
---
<!-- 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_50_v1_stsb
This model is a fine-tuned version of [Hartunka/bert_base_km_50_v1](https://huggingface.co/Hartunka/bert_base_km_50_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1389
- Pearson: 0.2763
- Spearmanr: 0.2801
- Combined Score: 0.2782
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.8402 | 1.0 | 23 | 2.4773 | 0.2068 | 0.2019 | 0.2043 |
| 2.0586 | 2.0 | 46 | 2.2433 | 0.2277 | 0.2264 | 0.2270 |
| 1.8469 | 3.0 | 69 | 2.1389 | 0.2763 | 0.2801 | 0.2782 |
| 1.5476 | 4.0 | 92 | 2.3079 | 0.2832 | 0.2836 | 0.2834 |
| 1.1654 | 5.0 | 115 | 2.3808 | 0.3015 | 0.3023 | 0.3019 |
| 0.8754 | 6.0 | 138 | 2.5276 | 0.2769 | 0.2751 | 0.2760 |
| 0.6215 | 7.0 | 161 | 2.4822 | 0.2907 | 0.2896 | 0.2901 |
| 0.4911 | 8.0 | 184 | 2.5762 | 0.3056 | 0.3060 | 0.3058 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1