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library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: tiny_bert_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: 0.2086240433941912
---
<!-- 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_5_v2_stsb
This model is a fine-tuned version of [Hartunka/tiny_bert_km_5_v2](https://huggingface.co/Hartunka/tiny_bert_km_5_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3479
- Pearson: 0.2208
- Spearmanr: 0.2086
- Combined Score: 0.2147
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.7925 | 1.0 | 23 | 2.3610 | 0.1193 | 0.1045 | 0.1119 |
| 2.0233 | 2.0 | 46 | 2.7265 | 0.1054 | 0.1047 | 0.1050 |
| 1.9375 | 3.0 | 69 | 2.3724 | 0.1641 | 0.1518 | 0.1580 |
| 1.8081 | 4.0 | 92 | 2.3479 | 0.2208 | 0.2086 | 0.2147 |
| 1.593 | 5.0 | 115 | 2.5032 | 0.2346 | 0.2337 | 0.2342 |
| 1.4271 | 6.0 | 138 | 2.3830 | 0.2663 | 0.2675 | 0.2669 |
| 1.2196 | 7.0 | 161 | 2.3673 | 0.3016 | 0.3058 | 0.3037 |
| 1.0511 | 8.0 | 184 | 2.5029 | 0.2915 | 0.2969 | 0.2942 |
| 0.9721 | 9.0 | 207 | 2.5246 | 0.2912 | 0.2977 | 0.2944 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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