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_v46
+  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_v46
+
+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: 1.8536
+- Rouge1: 0.485
+- Rouge2: 0.271
+- Rougel: 0.4374
+- Rougelsum: 0.4371
+- Bert precision: 0.8676
+- Bert recall: 0.8761
+- Average word count: 9.1032
+- Max word count: 17
+- Min word count: 4
+- Average token count: 15.8254
+- % shortened texts with length > 12: 9.5238
+
+## 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: 0.0003
+- train_batch_size: 32
+- eval_batch_size: 32
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:|
+| 1.8213        | 1.0   | 42   | 2.1030          | 0.4561 | 0.2433 | 0.4131 | 0.4131    | 0.8606         | 0.8724      | 9.0529             | 15             | 5              | 14.7249             | 7.4074                             |
+| 0.8874        | 2.0   | 84   | 1.8034          | 0.4778 | 0.2609 | 0.4316 | 0.4316    | 0.8569         | 0.8787      | 10.6323            | 21             | 5              | 16.2963             | 19.3122                            |
+| 0.603         | 3.0   | 126  | 1.6613          | 0.4749 | 0.2594 | 0.425  | 0.4253    | 0.8576         | 0.8796      | 10.5106            | 21             | 5              | 16.2751             | 23.0159                            |
+| 0.5413        | 4.0   | 168  | 1.5975          | 0.4729 | 0.249  | 0.4258 | 0.4254    | 0.8635         | 0.8696      | 8.6481             | 16             | 4              | 14.3677             | 4.2328                             |
+| 0.3393        | 5.0   | 210  | 1.6755          | 0.4959 | 0.28   | 0.4476 | 0.4473    | 0.8687         | 0.8772      | 8.8942             | 20             | 5              | 15.8915             | 8.4656                             |
+| 0.2573        | 6.0   | 252  | 1.6908          | 0.4775 | 0.2589 | 0.4309 | 0.4307    | 0.866          | 0.873       | 8.9868             | 22             | 4              | 15.4339             | 10.3175                            |
+| 0.173         | 7.0   | 294  | 1.8536          | 0.485  | 0.271  | 0.4374 | 0.4371    | 0.8676         | 0.8761      | 9.1032             | 17             | 4              | 15.8254             | 9.5238                             |
+
+
+### 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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