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language:
- en
base_model: Hartunka/tiny_bert_km_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: tiny_bert_km_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: 0.17557479397825773
---
<!-- 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. -->
# tiny_bert_km_100_v1_stsb
This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2017
- Pearson: 0.1983
- Spearmanr: 0.1756
- Combined Score: 0.1870
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.7897 | 1.0 | 23 | 2.2017 | 0.1983 | 0.1756 | 0.1870 |
| 2.1293 | 2.0 | 46 | 2.2599 | 0.2062 | 0.1845 | 0.1953 |
| 1.9869 | 3.0 | 69 | 2.3074 | 0.1839 | 0.1590 | 0.1715 |
| 1.8494 | 4.0 | 92 | 2.3755 | 0.2103 | 0.1966 | 0.2034 |
| 1.62 | 5.0 | 115 | 2.3458 | 0.2589 | 0.2531 | 0.2560 |
| 1.4033 | 6.0 | 138 | 2.3234 | 0.2691 | 0.2705 | 0.2698 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1
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