Text2Text Legal Clauses Finetuned Model
This model fine-tunes google/mt5-small model on shay681/Legal_Clauses dataset 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: [email protected]
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Model tree for shay681/Text2Text_Legal_Clauses_finetuned_model
Base model
google/mt5-small