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library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_100_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: tiny_bert_km_100_v2_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.29279076301228635
---
<!-- 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_v2_stsb
This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v2](https://huggingface.co/Hartunka/tiny_bert_km_100_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2118
- Pearson: 0.3037
- Spearmanr: 0.2928
- Combined Score: 0.2983
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.6374 | 1.0 | 23 | 2.2224 | 0.1110 | 0.1009 | 0.1060 |
| 2.0858 | 2.0 | 46 | 2.5104 | 0.1490 | 0.1353 | 0.1422 |
| 1.9616 | 3.0 | 69 | 2.2581 | 0.1995 | 0.1781 | 0.1888 |
| 1.8487 | 4.0 | 92 | 2.3268 | 0.2449 | 0.2255 | 0.2352 |
| 1.6866 | 5.0 | 115 | 2.4420 | 0.2440 | 0.2279 | 0.2359 |
| 1.5138 | 6.0 | 138 | 2.2118 | 0.3037 | 0.2928 | 0.2983 |
| 1.2926 | 7.0 | 161 | 2.4205 | 0.3232 | 0.3177 | 0.3204 |
| 1.0946 | 8.0 | 184 | 2.5488 | 0.3149 | 0.3092 | 0.3121 |
| 0.9053 | 9.0 | 207 | 2.5821 | 0.3028 | 0.2994 | 0.3011 |
| 0.7569 | 10.0 | 230 | 2.5048 | 0.3204 | 0.3157 | 0.3180 |
| 0.6373 | 11.0 | 253 | 2.5968 | 0.3135 | 0.3117 | 0.3126 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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