End of training

README.md

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+---
+base_model: google/pegasus-cnn_dailymail
+tags:
+- generated_from_trainer
+datasets:
+- billsum
+metrics:
+- rouge
+model-index:
+- name: pegasuscnn-dailymail_billsum_model
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: billsum
+      type: billsum
+      config: default
+      split: ca_test
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 0.4804
+---
+
+<!-- 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. -->
+
+# pegasuscnn-dailymail_billsum_model
+
+This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the billsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6747
+- Rouge1: 0.4804
+- Rouge2: 0.2362
+- Rougel: 0.3218
+- Rougelsum: 0.3218
+- Gen Len: 123.3669
+
+## 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: 5
+- eval_batch_size: 5
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
+| 2.6227        | 1.0   | 198  | 1.9091          | 0.4289 | 0.1938 | 0.2945 | 0.2947    | 120.1855 |
+| 1.9714        | 2.0   | 396  | 1.8147          | 0.4517 | 0.2093 | 0.3059 | 0.3061    | 120.7742 |
+| 1.903         | 3.0   | 594  | 1.7646          | 0.4607 | 0.2207 | 0.3098 | 0.3102    | 121.121  |
+| 1.7973        | 4.0   | 792  | 1.7362          | 0.4719 | 0.2264 | 0.3179 | 0.3178    | 122.3185 |
+| 1.7868        | 5.0   | 990  | 1.7137          | 0.4779 | 0.2314 | 0.3191 | 0.3192    | 123.2379 |
+| 1.7457        | 6.0   | 1188 | 1.6958          | 0.4748 | 0.2296 | 0.3171 | 0.317     | 123.2056 |
+| 1.6687        | 7.0   | 1386 | 1.6873          | 0.4795 | 0.2352 | 0.3216 | 0.3216    | 123.2702 |
+| 1.6751        | 8.0   | 1584 | 1.6806          | 0.4835 | 0.2384 | 0.3248 | 0.3245    | 122.8266 |
+| 1.6564        | 9.0   | 1782 | 1.6758          | 0.4814 | 0.2359 | 0.3217 | 0.3216    | 123.2984 |
+| 1.6333        | 10.0  | 1980 | 1.6747          | 0.4804 | 0.2362 | 0.3218 | 0.3218    | 123.3669 |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

generation_config.json

@@ -0,0 +1,12 @@
+{
+  "bos_token_id": 0,
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "forced_eos_token_id": 1,
+  "length_penalty": 0.8,
+  "max_length": 128,
+  "min_length": 32,
+  "num_beams": 8,
+  "pad_token_id": 0,
+  "transformers_version": "4.34.1"
+}

pytorch_model.bin

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