End of training
Browse files- README.md +76 -0
- generation_config.json +13 -0
- pytorch_model.bin +1 -1
README.md
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---
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license: mit
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base_model: facebook/bart-large-xsum
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tags:
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: text_shortening_model_v46
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# text_shortening_model_v46
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This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.8536
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- Rouge1: 0.485
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- Rouge2: 0.271
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- Rougel: 0.4374
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- Rougelsum: 0.4371
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- Bert precision: 0.8676
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- Bert recall: 0.8761
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- Average word count: 9.1032
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- Max word count: 17
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- Min word count: 4
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- Average token count: 15.8254
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- % shortened texts with length > 12: 9.5238
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0003
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 7
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### Training results
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| 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 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:|
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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### Framework versions
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- Transformers 4.33.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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generation_config.json
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{
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"early_stopping": true,
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"eos_token_id": 2,
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"forced_eos_token_id": 2,
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"max_length": 62,
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"min_length": 11,
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"no_repeat_ngram_size": 3,
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"num_beams": 6,
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"pad_token_id": 1,
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"transformers_version": "4.33.1"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 1625537293
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version https://git-lfs.github.com/spec/v1
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oid sha256:06ddaa362012e707d5b3cee5066c4d8f528f8896c82abd71afe203983890827a
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size 1625537293
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