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library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_10_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_rand_10_v1_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.2237898877305157
---
<!-- 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_rand_10_v1_stsb
This model is a fine-tuned version of [Hartunka/bert_base_rand_10_v1](https://huggingface.co/Hartunka/bert_base_rand_10_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3422
- Pearson: 0.2300
- Spearmanr: 0.2238
- Combined Score: 0.2269
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.5501 | 1.0 | 23 | 2.5206 | 0.1247 | 0.1086 | 0.1166 |
| 1.9123 | 2.0 | 46 | 2.3921 | 0.1624 | 0.1434 | 0.1529 |
| 1.6606 | 3.0 | 69 | 2.3422 | 0.2300 | 0.2238 | 0.2269 |
| 1.2907 | 4.0 | 92 | 2.5930 | 0.2617 | 0.2667 | 0.2642 |
| 0.9783 | 5.0 | 115 | 2.4709 | 0.2854 | 0.2803 | 0.2828 |
| 0.7673 | 6.0 | 138 | 2.4687 | 0.3073 | 0.3021 | 0.3047 |
| 0.5922 | 7.0 | 161 | 2.4917 | 0.3069 | 0.3033 | 0.3051 |
| 0.4832 | 8.0 | 184 | 2.7527 | 0.2931 | 0.2892 | 0.2911 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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