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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_tiny_lda_100_v1_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.22878969383272044
---
<!-- 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_tiny_lda_100_v1_stsb
This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3632
- Pearson: 0.2350
- Spearmanr: 0.2288
- Combined Score: 0.2319
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.8077 | 1.0 | 23 | 2.3850 | 0.0667 | 0.0654 | 0.0661 |
| 2.042 | 2.0 | 46 | 2.6089 | 0.0834 | 0.0848 | 0.0841 |
| 1.9254 | 3.0 | 69 | 2.3926 | 0.1539 | 0.1394 | 0.1466 |
| 1.8381 | 4.0 | 92 | 2.5560 | 0.1744 | 0.1720 | 0.1732 |
| 1.6974 | 5.0 | 115 | 3.0257 | 0.1812 | 0.1757 | 0.1784 |
| 1.5776 | 6.0 | 138 | 2.3632 | 0.2350 | 0.2288 | 0.2319 |
| 1.2951 | 7.0 | 161 | 2.4535 | 0.2594 | 0.2573 | 0.2584 |
| 1.0896 | 8.0 | 184 | 2.5246 | 0.2652 | 0.2622 | 0.2637 |
| 0.9372 | 9.0 | 207 | 2.9827 | 0.2716 | 0.2570 | 0.2643 |
| 0.7915 | 10.0 | 230 | 2.6918 | 0.3056 | 0.2926 | 0.2991 |
| 0.673 | 11.0 | 253 | 2.7520 | 0.3013 | 0.2887 | 0.2950 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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