transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/tinybert_train_book_v2 base_model:finetune:gokulsrinivasagan/tinybert_train_book_v2 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/tinybert_train_book_v2
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: tinybert_train_book_v2_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.809497912637751
      name: Spearmanr
---

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# tinybert_train_book_v2_stsb

This model is a fine-tuned version of [gokulsrinivasagan/tinybert_train_book_v2](https://huggingface.co/gokulsrinivasagan/tinybert_train_book_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7733
- Pearson: 0.8119
- Spearmanr: 0.8095
- Combined Score: 0.8107

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.0445        | 1.0   | 23   | 2.5260          | 0.0890  | 0.0888    | 0.0889         |
| 1.861         | 2.0   | 46   | 1.7447          | 0.5276  | 0.5175    | 0.5225         |
| 1.1901        | 3.0   | 69   | 1.1124          | 0.7331  | 0.7380    | 0.7356         |
| 0.8584        | 4.0   | 92   | 0.8622          | 0.7888  | 0.7846    | 0.7867         |
| 0.6948        | 5.0   | 115  | 0.9176          | 0.7912  | 0.7941    | 0.7927         |
| 0.5835        | 6.0   | 138  | 0.7733          | 0.8119  | 0.8095    | 0.8107         |
| 0.4936        | 7.0   | 161  | 0.8153          | 0.8118  | 0.8101    | 0.8110         |
| 0.4288        | 8.0   | 184  | 0.8134          | 0.8042  | 0.8021    | 0.8031         |
| 0.3747        | 9.0   | 207  | 0.8136          | 0.8064  | 0.8050    | 0.8057         |
| 0.3202        | 10.0  | 230  | 0.7878          | 0.8144  | 0.8125    | 0.8134         |
| 0.3003        | 11.0  | 253  | 0.8023          | 0.8134  | 0.8114    | 0.8124         |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
