update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- xlsum
+metrics:
+- rouge
+model-index:
+- name: t5-small-finetuned-xlsum-chinese-tradition
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: xlsum
+      type: xlsum
+      args: chinese_traditional
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 0.7966
+---
+
+<!-- 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-xlsum-chinese-tradition
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xlsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2848
+- Rouge1: 0.7966
+- Rouge2: 0.0942
+- Rougel: 0.7989
+- Rougelsum: 0.7967
+- Gen Len: 7.0854
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
+| 1.4457        | 1.0   | 2336 | 1.2848          | 0.7966 | 0.0942 | 0.7989 | 0.7967    | 7.0854  |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1