update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- wikihow
+metrics:
+- rouge
+model-index:
+- name: t5-small-finetuned-wikihow_3epoch_b8_lr3e-3
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: wikihow
+      type: wikihow
+      args: all
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 27.1711
+---
+
+<!-- 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-wikihow_3epoch_b8_lr3e-3
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikihow dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3163
+- Rouge1: 27.1711
+- Rouge2: 10.6296
+- Rougel: 23.206
+- Rougelsum: 26.4801
+- Gen Len: 18.5433
+
+## 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: 0.003
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| 3.0734        | 0.25  | 5000  | 2.7884          | 22.4825 | 7.2492  | 19.243  | 21.9167   | 18.0616 |
+| 2.9201        | 0.51  | 10000 | 2.7089          | 24.0869 | 8.0348  | 20.4814 | 23.4541   | 18.5994 |
+| 2.8403        | 0.76  | 15000 | 2.6390          | 24.62   | 8.3776  | 20.8736 | 23.9784   | 18.4676 |
+| 2.7764        | 1.02  | 20000 | 2.5943          | 24.1504 | 8.3933  | 20.8271 | 23.5382   | 18.4078 |
+| 2.6641        | 1.27  | 25000 | 2.5428          | 25.6574 | 9.2371  | 21.8576 | 24.9558   | 18.4249 |
+| 2.6369        | 1.53  | 30000 | 2.5042          | 25.5208 | 9.254   | 21.6673 | 24.8589   | 18.6467 |
+| 2.6           | 1.78  | 35000 | 2.4637          | 26.094  | 9.7003  | 22.3097 | 25.4695   | 18.5065 |
+| 2.5562        | 2.03  | 40000 | 2.4285          | 26.5374 | 9.9222  | 22.5291 | 25.8836   | 18.5553 |
+| 2.4322        | 2.29  | 45000 | 2.3858          | 26.939  | 10.3555 | 23.0211 | 26.2834   | 18.5614 |
+| 2.4106        | 2.54  | 50000 | 2.3537          | 26.7423 | 10.2816 | 22.7986 | 26.083    | 18.5792 |
+| 2.3731        | 2.8   | 55000 | 2.3163          | 27.1711 | 10.6296 | 23.206  | 26.4801   | 18.5433 |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.0.0
+- Tokenizers 0.11.6