Create README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- jsonl_dataset_sum.py
+metrics:
+- rouge
+model-index:
+- name: summarization_all
+  results:
+  - task:
+      name: Summarization
+      type: summarization
+    dataset:
+      name: jsonl_dataset_sum.py
+      type: jsonl_dataset_sum.py
+      config: 'null'
+      split: None
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 21.9857
+---
+
+<!-- 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. -->
+
+# summarization_all
+
+This model is a fine-tuned version of [KETI-AIR/long-ke-t5-base](https://huggingface.co/KETI-AIR/long-ke-t5-base) on the jsonl_dataset_sum.py dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1442
+- Rouge1: 21.9857
+- Rouge2: 10.2876
+- Rougel: 21.4026
+- Rougelsum: 21.4278
+- Gen Len: 86.2560
+
+## 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: 0.001
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 8
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step    | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| 1.2503        | 1.0   | 184670  | 1.2439          | 20.2525 | 9.1467  | 19.7454 | 19.771    | 87.1766 |
+| 1.1629        | 2.0   | 369340  | 1.1773          | 21.0068 | 9.6691  | 20.4565 | 20.4888   | 89.6074 |
+| 1.1087        | 3.0   | 554010  | 1.1431          | 21.0216 | 9.6545  | 20.489  | 20.5108   | 85.5895 |
+| 1.056         | 4.0   | 738680  | 1.1247          | 21.6776 | 10.1424 | 21.09   | 21.1168   | 89.6576 |
+| 1.0199        | 5.0   | 923350  | 1.1179          | 21.6563 | 10.0965 | 21.0814 | 21.1056   | 89.2454 |
+| 0.9652        | 6.0   | 1108020 | 1.1122          | 21.6209 | 10.0725 | 21.0623 | 21.0864   | 86.7079 |
+| 0.92          | 7.0   | 1292690 | 1.1136          | 21.9396 | 10.2734 | 21.3465 | 21.3745   | 86.5547 |
+| 0.8804        | 8.0   | 1477360 | 1.1228          | 21.8457 | 10.1858 | 21.2552 | 21.278    | 87.6413 |
+| 0.8447        | 9.0   | 1662030 | 1.1327          | 21.92   | 10.2635 | 21.3415 | 21.3633   | 86.4453 |
+| 0.7678        | 10.0  | 1846700 | 1.1442          | 21.9857 | 10.2876 | 21.4026 | 21.4278   | 86.2560 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.12.0
+- Datasets 2.8.0
+- Tokenizers 0.13.2