<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

bert-small-finetuned-legal-contracts-larger4010

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset.

Model description

More information needed

Intended uses & limitations

The model was not trained on the whole dataset which is around 9.5 GB, but only The first 40% of train + the last 10% of train.

datasets_train = load_dataset('albertvillanova/legal_contracts' , split='train[:40%]')
datasets_validation = load_dataset('albertvillanova/legal_contracts' , split='train[-10%:]')

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 128
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Framework versions

• Transformers 4.21.1
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1