metadata
language:
- en
base_model: Hartunka/tiny_bert_rand_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: tiny_bert_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: 0.11211697376930498
tiny_bert_rand_50_v1_stsb
This model is a fine-tuned version of Hartunka/tiny_bert_rand_50_v1 on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 2.2569
- Pearson: 0.1148
- Spearmanr: 0.1121
- Combined Score: 0.1135
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 3.4713 | 1.0 | 23 | 2.2569 | 0.1148 | 0.1121 | 0.1135 |
| 2.0275 | 2.0 | 46 | 2.6622 | 0.0980 | 0.0770 | 0.0875 |
| 1.8912 | 3.0 | 69 | 2.4156 | 0.1744 | 0.1615 | 0.1680 |
| 1.6966 | 4.0 | 92 | 2.5946 | 0.2103 | 0.2119 | 0.2111 |
| 1.4665 | 5.0 | 115 | 2.5630 | 0.2279 | 0.2358 | 0.2318 |
| 1.2375 | 6.0 | 138 | 2.5000 | 0.2583 | 0.2613 | 0.2598 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1