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--- |
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license: cc-by-nc-2.0 |
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base_model: facebook/opt-350m |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: tmp_trainer |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# tmp_trainer |
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This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the [addressWithContext](https://huggingface.co/datasets/piazzola/addressWithContext) dataset. |
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## Model description |
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**Make sure to set max_new_tokens = 20; otherwise, the model will generate one token at a time.** |
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``` |
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nlp = pipeline("text-generation", |
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model="piazzola/tmp_trainer", |
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max_new_tokens=20) |
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nlp("I live at 15 Firstfield Road.") |
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``` |
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**Note that if you would like to try longer sentences using the Hosted inference API |
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on the right hand side on this website, you might need to click "Compute" more than one time to get the address.** |
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## Intended uses & limitations |
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The model is intended to detect addresses that occur in a sentence. |
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## Training and evaluation data |
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This model is trained on `piazzola/addressWithContext`. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
