T5-base-finetuned-stsb

This model is T5 fine-tuned on GLUE STS-B dataset. It acheives the following results on the validation set

• Pearson Correlation Coefficient: 0.8937

Model Details

T5 is an encoder-decoder model pre-trained on a multi-task mixture of unsupervised and supervised tasks and for which each task is converted into a text-to-text format.

Training procedure

Tokenization

Since, T5 is a text-to-text model, the labels of the dataset are converted as follows: For each example, a sentence as been formed as "stsb sentence1: " + stsb_sent1 + "sentence2: " + stsb_sent2 and fed to the tokenizer to get the input_ids and attention_mask. Unlike other GLUE tasks, STS-B is a regression task where the goal is to predict a similarity score between 1 and 5. I have used the same stratey as descibed in the T5 paper for fine-tuning. In the paper, it is mentioned as

regression problem as a 21-class classification problem. ```


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-4
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: epsilon=1e-08
- num_epochs: 3.0

### Training results


|Epoch | Training Loss | Validation Pearson Correlation Coefficient |
|:----:|:-------------:|:-------------------:|
|   1  |    0.8623     | 0.8200           |
|   2  |    0.7782     | 0.8675        |
|   3  |     0.7040   | **0.8937** |