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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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Base model
google/mt5-small