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library_name: transformers
language:
- en
base_model: Hartunka/distilbert_rand_10_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: distilbert_rand_10_v2_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.3015093929726957
---
<!-- 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. -->
# distilbert_rand_10_v2_stsb
This model is a fine-tuned version of [Hartunka/distilbert_rand_10_v2](https://huggingface.co/Hartunka/distilbert_rand_10_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2101
- Pearson: 0.3094
- Spearmanr: 0.3015
- Combined Score: 0.3055
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.7267 | 1.0 | 23 | 2.4802 | 0.1260 | 0.1086 | 0.1173 |
| 1.9118 | 2.0 | 46 | 2.4211 | 0.2286 | 0.2110 | 0.2198 |
| 1.6277 | 3.0 | 69 | 2.2101 | 0.3094 | 0.3015 | 0.3055 |
| 1.3088 | 4.0 | 92 | 2.2704 | 0.3073 | 0.3050 | 0.3062 |
| 1.0113 | 5.0 | 115 | 2.4404 | 0.3233 | 0.3195 | 0.3214 |
| 0.7442 | 6.0 | 138 | 2.2811 | 0.3766 | 0.3775 | 0.3770 |
| 0.5763 | 7.0 | 161 | 2.3778 | 0.3448 | 0.3449 | 0.3449 |
| 0.4382 | 8.0 | 184 | 2.5305 | 0.3544 | 0.3537 | 0.3541 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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