update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- gigaword
+metrics:
+- rouge
+model-index:
+- name: t5-small-finetuned-giga
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: gigaword
+      type: gigaword
+      config: default
+      split: train[:10%]
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 26.6579
+---
+
+<!-- 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-giga
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the gigaword dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.2594
+- Rouge1: 26.6579
+- Rouge2: 9.5505
+- Rougel: 24.4987
+- Rougelsum: 24.5146
+- Gen Len: 13.5436
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 1.8512        | 1.0   | 23775 | 3.2594          | 26.6579 | 9.5505 | 24.4987 | 24.5146   | 13.5436 |
+
+
+### Framework versions
+
+- Transformers 4.24.0
+- Pytorch 1.12.1+cu113
+- Datasets 2.7.1
+- Tokenizers 0.13.2