Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-license: openrail
+license: apache-2.0
 tags:
 - generated_from_trainer
 datasets:
@@ -29,6 +29,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 # base
 
+![model image](https://s3.amazonaws.com/moonup/production/uploads/1666363435475-62441d1d9fdefb55a0b7d12c.png)
+
 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.
 It achieves the following results on the evaluation set:
 - Loss: 1.4232
@@ -40,17 +42,34 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+- **Model type:** Language model
+- **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
+- **License:** Apache 2.0
+- **Related Models:** [All FLAN-T5 Checkpoints](https://huggingface.co/models?search=flan-t5)
+- **Original Checkpoints:** [All Original FLAN-T5 Checkpoints](https://github.com/google-research/t5x/blob/main/docs/models.md#flan-t5-checkpoints)
+- **Resources for more information:**
+  - [Research paper](https://arxiv.org/pdf/2210.11416.pdf)
+  - [GitHub Repo](https://github.com/google-research/t5x)
+  - [Hugging Face FLAN-T5 Docs (Similar to T5) ](https://huggingface.co/docs/transformers/model_doc/t5)
 
 ## Intended uses & limitations
 
-More information needed
+The information below in this section are copied from the model's [official model card](https://arxiv.org/pdf/2210.11416.pdf):
+
+> 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,
 
 ## Training and evaluation data
 
-More information needed
+- Loss: 1.4232
+- Rouge1: 42.1388
+- Rouge2: 19.7696
+- Rougel: 30.1512
+- Rougelsum: 39.3222
+- Gen Len: 71.8562
 
 ## Training procedure
+Training procedure example notebook for flan-T5 and pushing it to hub
+[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)
 
 ### Training hyperparameters