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_v49
+  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_v49
+
+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: 1.7760
+- Rouge1: 0.5119
+- Rouge2: 0.2768
+- Rougel: 0.4448
+- Rougelsum: 0.4444
+- Bert precision: 0.8755
+- Bert recall: 0.8801
+- Average word count: 8.8492
+- Max word count: 20
+- Min word count: 5
+- Average token count: 16.4709
+- % shortened texts with length > 12: 8.7302
+
+## 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: 0.0001
+- 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: 5
+
+### 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:|
+| 1.8542        | 1.0   | 83   | 1.6189          | 0.5121 | 0.2699 | 0.4302 | 0.4304    | 0.863          | 0.8909      | 11.3386            | 21             | 5              | 19.4312             | 31.746                             |
+| 0.9651        | 2.0   | 166  | 1.4837          | 0.4957 | 0.2664 | 0.4347 | 0.4362    | 0.8687         | 0.8758      | 8.8598             | 19             | 4              | 16.9815             | 9.2593                             |
+| 0.608         | 3.0   | 249  | 1.4074          | 0.5012 | 0.2693 | 0.4346 | 0.4342    | 0.8725         | 0.8781      | 8.836              | 20             | 4              | 15.5265             | 5.5556                             |
+| 0.3788        | 4.0   | 332  | 1.5646          | 0.5202 | 0.2836 | 0.4535 | 0.4537    | 0.876          | 0.881       | 8.9312             | 18             | 5              | 16.4365             | 10.3175                            |
+| 0.2296        | 5.0   | 415  | 1.7760          | 0.5119 | 0.2768 | 0.4448 | 0.4444    | 0.8755         | 0.8801      | 8.8492             | 20             | 5              | 16.4709             | 8.7302                             |
+
+
+### 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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