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library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_rand_50_v1_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.25999577762490267
---
<!-- 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_50_v1_stsb
This model is a fine-tuned version of [Hartunka/bert_base_rand_50_v1](https://huggingface.co/Hartunka/bert_base_rand_50_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2715
- Pearson: 0.2635
- Spearmanr: 0.2600
- Combined Score: 0.2618
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.0174 | 1.0 | 23 | 2.9030 | 0.0773 | 0.0674 | 0.0724 |
| 2.0319 | 2.0 | 46 | 2.4340 | 0.1690 | 0.1495 | 0.1593 |
| 1.7905 | 3.0 | 69 | 2.3889 | 0.2034 | 0.1918 | 0.1976 |
| 1.467 | 4.0 | 92 | 2.2715 | 0.2635 | 0.2600 | 0.2618 |
| 1.1681 | 5.0 | 115 | 2.4279 | 0.2436 | 0.2402 | 0.2419 |
| 1.0229 | 6.0 | 138 | 2.8679 | 0.2669 | 0.2723 | 0.2696 |
| 0.7645 | 7.0 | 161 | 2.5480 | 0.2725 | 0.2734 | 0.2730 |
| 0.6161 | 8.0 | 184 | 2.8213 | 0.2753 | 0.2854 | 0.2804 |
| 0.4918 | 9.0 | 207 | 2.5409 | 0.2620 | 0.2639 | 0.2630 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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