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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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datasets: |
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- cnn_dailymail |
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metrics: |
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- rouge |
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model-index: |
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- name: base |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: cnn_dailymail 3.0.0 |
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type: cnn_dailymail |
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config: 3.0.0 |
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split: validation |
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args: 3.0.0 |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 42.1388 |
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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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# base |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the cnn_dailymail 3.0.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4232 |
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- Rouge1: 42.1388 |
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- Rouge2: 19.7696 |
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- Rougel: 30.1512 |
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- Rougelsum: 39.3222 |
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- Gen Len: 71.8562 |
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## Model description |
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- **Model type:** Language model |
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- **Language(s) (NLP):** English, Spanish, Japanese, Persian, Hindi, French, Chinese, Bengali, Gujarati, German, Telugu, Italian, Arabic, Polish, Tamil, Marathi, Malayalam, Oriya, Panjabi, Portuguese, Urdu, Galician, Hebrew, Korean, Catalan, Thai, Dutch, Indonesian, Vietnamese, Bulgarian, Filipino, Central Khmer, Lao, Turkish, Russian, Croatian, Swedish, Yoruba, Kurdish, Burmese, Malay, Czech, Finnish, Somali, Tagalog, Swahili, Sinhala, Kannada, Zhuang, Igbo, Xhosa, Romanian, Haitian, Estonian, Slovak, Lithuanian, Greek, Nepali, Assamese, Norwegian |
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- **License:** Apache 2.0 |
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- **Related Models:** [All FLAN-T5 Checkpoints](https://huggingface.co/models?search=flan-t5) |
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- **Original Checkpoints:** [All Original FLAN-T5 Checkpoints](https://github.com/google-research/t5x/blob/main/docs/models.md#flan-t5-checkpoints) |
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- **Resources for more information:** |
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- [Research paper](https://arxiv.org/pdf/2210.11416.pdf) |
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- [GitHub Repo](https://github.com/google-research/t5x) |
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- [Hugging Face FLAN-T5 Docs (Similar to T5) ](https://huggingface.co/docs/transformers/model_doc/t5) |
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## Intended uses & limitations |
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The information below in this section are copied from the model's [official model card](https://arxiv.org/pdf/2210.11416.pdf): |
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> Language models, including Flan-T5, can potentially be used for language generation in a harmful way, according to Rae et al. (2021). Flan-T5 should not be used directly in any application, |
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## Training and evaluation data |
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- Loss: 1.4232 |
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- Rouge1: 42.1388 |
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- Rouge2: 19.7696 |
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- Rougel: 30.1512 |
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- Rougelsum: 39.3222 |
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- Gen Len: 71.8562 |
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## Training procedure |
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Training procedure example notebook for flan-T5 and pushing it to hub |
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[https://github.com/EveripediaNetwork/ai/blob/main/notebooks/Fine-Tuning-Flan-T5_1.ipynb](https://github.com/EveripediaNetwork/ai/blob/main/notebooks/Fine-Tuning-Flan-T5_1.ipynb) |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: Constant |
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- num_epochs: 3.0 |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.12.1 |
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--- |
