update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- summarization
+- generated_from_trainer
+datasets:
+- samsum
+metrics:
+- rouge
+model-index:
+- name: t5-small-finetuned-samsum-en
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: samsum
+      type: samsum
+      args: samsum
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 42.3215
+---
+
+<!-- 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-samsum-en
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the samsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7863
+- Rouge1: 42.3215
+- Rouge2: 19.4644
+- Rougel: 35.3715
+- Rougelsum: 39.1274
+
+## 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: 10
+- eval_batch_size: 10
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
+| 2.2448        | 1.0   | 300  | 1.8993          | 39.5059 | 17.0654 | 32.9974 | 36.6153   |
+| 2.0428        | 2.0   | 600  | 1.8499          | 40.0529 | 17.4367 | 33.4804 | 37.057    |
+| 1.9626        | 3.0   | 900  | 1.8278          | 40.7994 | 17.918  | 34.0773 | 37.6219   |
+| 1.8992        | 4.0   | 1200 | 1.8118          | 41.3782 | 18.5579 | 34.7794 | 38.4994   |
+| 1.8429        | 5.0   | 1500 | 1.8006          | 41.8624 | 18.7592 | 34.9262 | 38.7019   |
+| 1.8057        | 6.0   | 1800 | 1.7988          | 41.1316 | 18.5242 | 34.7271 | 38.2821   |
+| 1.775         | 7.0   | 2100 | 1.7856          | 42.2036 | 19.3343 | 35.4442 | 39.2114   |
+| 1.7376        | 8.0   | 2400 | 1.7797          | 41.9569 | 18.9482 | 35.1953 | 38.7609   |
+| 1.7096        | 9.0   | 2700 | 1.7780          | 42.6065 | 19.2152 | 35.4563 | 39.2736   |
+| 1.6885        | 10.0  | 3000 | 1.7826          | 42.1595 | 18.8477 | 34.8679 | 38.9388   |
+| 1.6581        | 11.0  | 3300 | 1.7809          | 42.291  | 19.0846 | 35.1938 | 38.894    |
+| 1.6392        | 12.0  | 3600 | 1.7824          | 42.3588 | 19.4507 | 35.4588 | 39.2067   |
+| 1.6258        | 13.0  | 3900 | 1.7806          | 42.0932 | 19.002  | 35.0112 | 38.8053   |
+| 1.6042        | 14.0  | 4200 | 1.7828          | 42.0564 | 19.3141 | 35.2479 | 38.8301   |
+| 1.5993        | 15.0  | 4500 | 1.7824          | 42.6056 | 19.5164 | 35.4112 | 39.2322   |
+| 1.5869        | 16.0  | 4800 | 1.7839          | 42.1505 | 19.1529 | 35.0853 | 38.8788   |
+| 1.5778        | 17.0  | 5100 | 1.7827          | 42.5416 | 19.5103 | 35.5507 | 39.293    |
+| 1.5716        | 18.0  | 5400 | 1.7865          | 42.3028 | 19.3783 | 35.3466 | 39.0594   |
+| 1.5615        | 19.0  | 5700 | 1.7857          | 42.4001 | 19.5111 | 35.4686 | 39.1614   |
+| 1.5606        | 20.0  | 6000 | 1.7863          | 42.3215 | 19.4644 | 35.3715 | 39.1274   |
+
+
+### Framework versions
+
+- Transformers 4.19.2
+- Pytorch 1.11.0+cu113
+- Datasets 2.2.2
+- Tokenizers 0.12.1