update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- xsum
+metrics:
+- rouge
+model-index:
+- name: t5-small-finetuned-xsum-wei2
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: xsum
+      type: xsum
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 29.2287
+---
+
+<!-- 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-wei2
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.4131
+- Rouge1: 29.2287
+- Rouge2: 8.4073
+- Rougel: 23.0934
+- Rougelsum: 23.0954
+- Gen Len: 18.8236
+
+## 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: 4e-05
+- train_batch_size: 12
+- eval_batch_size: 12
+- 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 2.633         | 1.0   | 17004 | 2.4131          | 29.2287 | 8.4073 | 23.0934 | 23.0954   | 18.8236 |
+
+
+### Framework versions
+
+- Transformers 4.11.3
+- Pytorch 1.9.0+cu111
+- Datasets 1.14.0
+- Tokenizers 0.10.3