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-4
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: wikihow
+      type: wikihow
+      args: all
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 27.3718
+---
+
+<!-- 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-4
+
+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: 2.3136
+- Rouge1: 27.3718
+- Rouge2: 10.6235
+- Rougel: 23.3396
+- Rougelsum: 26.6889
+- Gen Len: 18.5194
+
+## 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: 0.0003
+- 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| 2.8029        | 0.25  | 5000  | 2.5368          | 25.2267 | 8.9048  | 21.2588 | 24.5804   | 18.4303 |
+| 2.6924        | 0.51  | 10000 | 2.4725          | 25.6553 | 9.1904  | 21.7633 | 24.9807   | 18.5549 |
+| 2.6369        | 0.76  | 15000 | 2.4332          | 26.2895 | 9.7203  | 22.3286 | 25.6009   | 18.4185 |
+| 2.5994        | 1.02  | 20000 | 2.4051          | 26.1779 | 9.5708  | 22.3531 | 25.5357   | 18.561  |
+| 2.521         | 1.27  | 25000 | 2.3805          | 26.7558 | 10.0411 | 22.7252 | 26.0476   | 18.304  |
+| 2.5091        | 1.53  | 30000 | 2.3625          | 26.6439 | 10.0698 | 22.6662 | 25.9537   | 18.5437 |
+| 2.4941        | 1.78  | 35000 | 2.3498          | 26.9322 | 10.2817 | 23.0002 | 26.2604   | 18.4953 |
+| 2.4848        | 2.03  | 40000 | 2.3424          | 27.0381 | 10.3452 | 22.9749 | 26.3407   | 18.5749 |
+| 2.4268        | 2.29  | 45000 | 2.3272          | 27.2386 | 10.4595 | 23.1866 | 26.5541   | 18.4954 |
+| 2.4263        | 2.54  | 50000 | 2.3226          | 27.1489 | 10.532  | 23.1428 | 26.4657   | 18.5583 |
+| 2.4161        | 2.8   | 55000 | 2.3136          | 27.3718 | 10.6235 | 23.3396 | 26.6889   | 18.5194 |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.0.0
+- Tokenizers 0.11.6