YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Text2Text Precedents Finetuned Model

This model fine-tunes google/mt5-small model on shay681/Precedents dataset.

Training and evaluation data

Dataset Split # samples
Precedents train 473,204
Precedents validation 118,302

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 0.075
F1 0.024

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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Dataset used to train shay681/Text2Text_Precedents_finetuned_model