File size: 3,283 Bytes
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library_name: transformers
language:
- en
license: apache-2.0
base_model: gokulsrinivasagan/tinybert_base_train_kd
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: tinybert_base_train_kd_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.8229059501737404
---
<!-- 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. -->
# tinybert_base_train_kd_stsb
This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_kd](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_kd) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7127
- Pearson: 0.8275
- Spearmanr: 0.8229
- Combined Score: 0.8252
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.613 | 1.0 | 23 | 2.5624 | 0.1145 | 0.1287 | 0.1216 |
| 1.8186 | 2.0 | 46 | 1.1171 | 0.7169 | 0.7142 | 0.7155 |
| 1.1222 | 3.0 | 69 | 1.0925 | 0.7803 | 0.7822 | 0.7813 |
| 0.8374 | 4.0 | 92 | 0.7486 | 0.8170 | 0.8122 | 0.8146 |
| 0.7145 | 5.0 | 115 | 0.7349 | 0.8232 | 0.8204 | 0.8218 |
| 0.5299 | 6.0 | 138 | 0.7158 | 0.8318 | 0.8265 | 0.8292 |
| 0.4359 | 7.0 | 161 | 0.7249 | 0.8288 | 0.8267 | 0.8278 |
| 0.3798 | 8.0 | 184 | 0.7129 | 0.8281 | 0.8235 | 0.8258 |
| 0.3253 | 9.0 | 207 | 0.7902 | 0.8171 | 0.8150 | 0.8161 |
| 0.277 | 10.0 | 230 | 0.7336 | 0.8229 | 0.8195 | 0.8212 |
| 0.255 | 11.0 | 253 | 0.7127 | 0.8275 | 0.8229 | 0.8252 |
| 0.2257 | 12.0 | 276 | 0.7646 | 0.8233 | 0.8216 | 0.8225 |
| 0.204 | 13.0 | 299 | 0.8714 | 0.8245 | 0.8235 | 0.8240 |
| 0.1957 | 14.0 | 322 | 0.7891 | 0.8213 | 0.8179 | 0.8196 |
| 0.1725 | 15.0 | 345 | 0.7348 | 0.8230 | 0.8193 | 0.8212 |
| 0.1621 | 16.0 | 368 | 0.7909 | 0.8179 | 0.8149 | 0.8164 |
### Framework versions
- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
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