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: mt5-small-finetuned-tradition-zh
+  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: 5.7605
+---
+
+<!-- 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. -->
+
+# mt5-small-finetuned-tradition-zh
+
+This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xlsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.9218
+- Rouge1: 5.7605
+- Rouge2: 1.2779
+- Rougel: 5.7527
+- Rougelsum: 5.7517
+
+## 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: 5.6e-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: 6
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
+| 4.542         | 1.0   | 2336  | 3.1979          | 4.8399 | 1.0214 | 4.8134 | 4.8158    |
+| 3.7542        | 2.0   | 4672  | 3.0662          | 5.2183 | 1.1035 | 5.2097 | 5.1999    |
+| 3.5706        | 3.0   | 7008  | 3.0070          | 5.5365 | 1.3477 | 5.5316 | 5.5173    |
+| 3.4668        | 4.0   | 9344  | 2.9537          | 5.5813 | 1.1682 | 5.5661 | 5.5649    |
+| 3.4082        | 5.0   | 11680 | 2.9391          | 5.8047 | 1.3486 | 5.783  | 5.7917    |
+| 3.375         | 6.0   | 14016 | 2.9218          | 5.7605 | 1.2779 | 5.7527 | 5.7517    |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1