End of training

README.md

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+---
+license: apache-2.0
+base_model: allenai/led-base-16384
+tags:
+- generated_from_trainer
+datasets:
+- billsum
+metrics:
+- rouge
+model-index:
+- name: LED_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: 0.1447
+---
+
+<!-- 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. -->
+
+# LED_billsum_model
+
+This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the billsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6576
+- Rouge1: 0.1447
+- Rouge2: 0.0854
+- Rougel: 0.1292
+- Rougelsum: 0.1339
+- Gen Len: 20.0
+
+## 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: 3
+- eval_batch_size: 3
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
+| 1.4849        | 1.0   | 330  | 1.6511          | 0.1463 | 0.0827 | 0.1276 | 0.1337    | 20.0    |
+| 1.3361        | 2.0   | 660  | 1.6056          | 0.148  | 0.0799 | 0.1268 | 0.1336    | 20.0    |
+| 1.1727        | 3.0   | 990  | 1.5833          | 0.1459 | 0.0827 | 0.1289 | 0.1341    | 20.0    |
+| 1.0601        | 4.0   | 1320 | 1.5987          | 0.1462 | 0.0859 | 0.1299 | 0.1344    | 20.0    |
+| 0.9789        | 5.0   | 1650 | 1.6030          | 0.1414 | 0.0794 | 0.125  | 0.1302    | 20.0    |
+| 0.8724        | 6.0   | 1980 | 1.6060          | 0.1476 | 0.0868 | 0.1298 | 0.1356    | 20.0    |
+| 0.7994        | 7.0   | 2310 | 1.6295          | 0.1348 | 0.0758 | 0.1198 | 0.1253    | 20.0    |
+| 0.7762        | 8.0   | 2640 | 1.6317          | 0.1422 | 0.0831 | 0.1261 | 0.1312    | 20.0    |
+| 0.7087        | 9.0   | 2970 | 1.6501          | 0.1421 | 0.0825 | 0.1264 | 0.1311    | 20.0    |
+| 0.7014        | 10.0  | 3300 | 1.6576          | 0.1447 | 0.0854 | 0.1292 | 0.1339    | 20.0    |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

generation_config.json

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+{
+  "bos_token_id": 0,
+  "decoder_start_token_id": 2,
+  "eos_token_id": 2,
+  "pad_token_id": 1,
+  "transformers_version": "4.34.1"
+}

pytorch_model.bin

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