metadata
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_rand_10_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: tiny_bert_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: 0.11027095360407262
tiny_bert_rand_10_v2_stsb
This model is a fine-tuned version of Hartunka/tiny_bert_rand_10_v2 on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 2.2278
- Pearson: 0.1029
- Spearmanr: 0.1103
- Combined Score: 0.1066
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 |
|---|---|---|---|---|---|---|
| 3.1623 | 1.0 | 23 | 2.2278 | 0.1029 | 0.1103 | 0.1066 |
| 2.0283 | 2.0 | 46 | 2.6435 | 0.0808 | 0.0590 | 0.0699 |
| 1.8414 | 3.0 | 69 | 2.4582 | 0.1896 | 0.1824 | 0.1860 |
| 1.6228 | 4.0 | 92 | 2.4701 | 0.2441 | 0.2441 | 0.2441 |
| 1.3269 | 5.0 | 115 | 2.4297 | 0.2678 | 0.2654 | 0.2666 |
| 1.0809 | 6.0 | 138 | 2.4510 | 0.2983 | 0.3000 | 0.2992 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1