---
datasets:
- shay681/Legal_Clauses
language:
- he
base_model:
- google/mt5-small
pipeline_tag: text2text-generation
---
# Text2Text Legal Clauses Finetuned Model

This model fine-tunes [google/mt5-small](https://huggingface.co/google/mt5-small) model on [shay681/Legal_Clauses dataset](https://huggingface.co/datasets/shay681/Legal_Clauses) dataset.


## Training and evaluation data

| Dataset  | Split | # samples |
| -------- | ----- | --------- |
| Legal_Clauses | train | 147,946 |
| Legal_Clauses | validation | 36,987 |


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- evaluation_strategy: "epoch"
- learning_rate: 5e-5
- train_batch_size: 4
- eval_batch_size: 4
- num_train_epochs: 5
- weight_decay: 0.01


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6


### Results

| Metric | # Value   |
| ------ | --------- |
| **Accuracy** | **0.87** | 
| **F1** | **0.64** |


### About Me
Created by Shay Doner.
This is my final project as part of intelligent systems M.Sc studies at Afeka College in Tel-Aviv.
For more cooperation, please contact email: 
shay681@gmail.com