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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- email generation |
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- email |
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datasets: |
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- aeslc |
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- postbot/multi_emails_kw |
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widget: |
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- text: Thursday pay invoice need asap thanks Pierre good morning dear Harold |
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example_title: invoice |
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- text: dear elia when will space be ready need urgently regards ronald |
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example_title: space ready |
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- text: Tuesday need talk with you important stuff dear jonathan status war in Syria |
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example_title: war status |
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- text: dear bob will back wednesday need urgently regards elena |
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example_title: return wednesday |
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- text: dear mary thanks for your last invoice need know when payment be |
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example_title: last invoice |
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- text: pct1_dropremainder rounding may truncate the last examples in a dataset if |
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the number of examples in your dataset don’t divide evenly by 100 dear bob |
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example_title: pct1_dropremainder |
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- text: dear joseph have all invoices ready Monday next invoice in 30 days have great |
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weekend |
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example_title: next invoice |
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- text: dear mary I have couple questions on new contract we agreed on need know thoughts |
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regarding contract |
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example_title: contract |
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- text: Friday will make report due soon please thanks dear john |
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example_title: report due soon |
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- text: need take photos sunday want finish thursday photo exhibition need urgent |
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help thanks dear john |
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example_title: photo exhibition |
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- text: Tuesday need talk with you important stuff dear reginald |
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example_title: important talk |
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- text: dear maria how are you doing thanks very much |
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example_title: thanks |
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- text: dear james tomorrow will prepare file for june report before leave need know |
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when leave |
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example_title: file for june report |
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parameters: |
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min_length: 16 |
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max_length: 256 |
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no_repeat_ngram_size: 2 |
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do_sample: false |
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num_beams: 8 |
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early_stopping: true |
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repetition_penalty: 5.5 |
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length_penalty: 0.9 |
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base_model: pszemraj/t5-base-kw2email-v3.5 |
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--- |
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# t5-base-kw2email-v4 |
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This version **improves on prior "base" versions** by using training hyperparameters more closely aligned with [bigscience/T0](https://huggingface.co/bigscience/T0) |
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This model is a fine-tuned version of [pszemraj/t5-base-kw2email-v3.5](https://huggingface.co/pszemraj/t5-base-kw2email-v3.5) on the None dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 8 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 2 |
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### Training results |
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### Framework versions |
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- Transformers 4.21.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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