End of training

README.md

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+---
+license: mit
+base_model: facebook/bart-large-xsum
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: text_shortening_model_v47
+  results: []
+---
+
+<!-- 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. -->
+
+# text_shortening_model_v47
+
+This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 6.3912
+- Rouge1: 0.0
+- Rouge2: 0.0
+- Rougel: 0.0
+- Rougelsum: 0.0
+- Bert precision: 0.6047
+- Bert recall: 0.5681
+- Average word count: 1.0
+- Max word count: 1
+- Min word count: 1
+- Average token count: 12.0
+- % shortened texts with length > 12: 0.0
+
+## 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: 0.005
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bert precision | Bert recall | Average word count | Max word count | Min word count | Average token count | % shortened texts with length > 12 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:|
+| 7.822         | 1.0   | 83   | 7.4737          | 0.0776 | 0.0    | 0.0775 | 0.0776    | 0.6348         | 0.6223      | 2.0                | 2              | 2              | 13.0                | 0.0                                |
+| 3.2859        | 2.0   | 166  | 6.6585          | 0.1063 | 0.0    | 0.1063 | 0.1063    | 0.6469         | 0.608       | 5.0026             | 6              | 5              | 12.0                | 0.0                                |
+| 3.0284        | 3.0   | 249  | 6.4761          | 0.116  | 0.0    | 0.116  | 0.1161    | 0.6479         | 0.6388      | 3.9974             | 4              | 3              | 14.0                | 0.0                                |
+| 2.9681        | 4.0   | 332  | 6.4592          | 0.0    | 0.0    | 0.0    | 0.0       | 0.6071         | 0.5723      | 1.0                | 1              | 1              | 12.0                | 0.0                                |
+| 2.9377        | 5.0   | 415  | 6.4142          | 0.0    | 0.0    | 0.0    | 0.0       | 0.6047         | 0.5681      | 1.0                | 1              | 1              | 12.0                | 0.0                                |
+| 2.9168        | 6.0   | 498  | 6.4049          | 0.0    | 0.0    | 0.0    | 0.0       | 0.6049         | 0.5685      | 1.0                | 1              | 1              | 12.0                | 0.0                                |
+| 2.8964        | 7.0   | 581  | 6.3912          | 0.0    | 0.0    | 0.0    | 0.0       | 0.6047         | 0.5681      | 1.0                | 1              | 1              | 12.0                | 0.0                                |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "bos_token_id": 0,
+  "decoder_start_token_id": 2,
+  "early_stopping": true,
+  "eos_token_id": 2,
+  "forced_eos_token_id": 2,
+  "max_length": 62,
+  "min_length": 11,
+  "no_repeat_ngram_size": 3,
+  "num_beams": 6,
+  "pad_token_id": 1,
+  "transformers_version": "4.33.1"
+}

pytorch_model.bin

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