update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- multi_news
+metrics:
+- rouge
+model-index:
+- name: t5-small-finetuned-xsum-ashishkhandelwal
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: multi_news
+      type: multi_news
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 14.7089
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# t5-small-finetuned-xsum-ashishkhandelwal
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the multi_news dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.7453
+- Rouge1: 14.7089
+- Rouge2: 4.6798
+- Rougel: 11.2024
+- Rougelsum: 13.0025
+- Gen Len: 18.9968
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 2.9805        | 1.0   | 2811 | 2.7453          | 14.7089 | 4.6798 | 11.2024 | 13.0025   | 18.9968 |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.12.1+cu113
+- Datasets 2.6.1
+- Tokenizers 0.13.1