OATH Frames
Collection
Datasets and Models for the paper titled: OATH-Frames: Characterizing Online Attitudes towards Homelessness with LLM Assistants. • 11 items • Updated
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OATH Frames - Flan T5 Base
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dill-lab/oath-frames-flant5-base") model = AutoModelForSeq2SeqLM.from_pretrained("dill-lab/oath-frames-flant5-base")