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library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_km_5_v1_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.3215629379042137
---
<!-- 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_v1_stsb
This model is a fine-tuned version of [Hartunka/bert_base_km_5_v1](https://huggingface.co/Hartunka/bert_base_km_5_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2394
- Pearson: 0.3227
- Spearmanr: 0.3216
- Combined Score: 0.3221
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.6517 | 1.0 | 23 | 2.3255 | 0.1330 | 0.1205 | 0.1268 |
| 1.9658 | 2.0 | 46 | 2.3461 | 0.2386 | 0.2286 | 0.2336 |
| 1.6725 | 3.0 | 69 | 2.4374 | 0.2424 | 0.2349 | 0.2387 |
| 1.2633 | 4.0 | 92 | 2.2394 | 0.3227 | 0.3216 | 0.3221 |
| 0.877 | 5.0 | 115 | 2.4882 | 0.3102 | 0.3147 | 0.3125 |
| 0.6898 | 6.0 | 138 | 2.4795 | 0.3147 | 0.3068 | 0.3107 |
| 0.4742 | 7.0 | 161 | 2.6675 | 0.2998 | 0.2927 | 0.2963 |
| 0.3676 | 8.0 | 184 | 2.3370 | 0.3624 | 0.3603 | 0.3614 |
| 0.3107 | 9.0 | 207 | 2.4862 | 0.3395 | 0.3334 | 0.3364 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
|