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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
model-index:
- name: text_shortening_model_v72
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_v72
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6295
- Bert precision: 0.9015
- Bert recall: 0.9003
- Bert f1-score: 0.9004
- Average word count: 6.4845
- Max word count: 16
- Min word count: 2
- Average token count: 10.5656
- % shortened texts with length > 12: 1.1011
## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bert precision | Bert recall | Bert f1-score | Average word count | Max word count | Min word count | Average token count | % shortened texts with length > 12 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:|
| 1.6981 | 1.0 | 37 | 1.2099 | 0.8879 | 0.8868 | 0.8868 | 6.5786 | 15 | 1 | 10.3994 | 0.8008 |
| 1.1993 | 2.0 | 74 | 1.1320 | 0.8939 | 0.89 | 0.8914 | 6.3013 | 16 | 2 | 10.2663 | 0.9009 |
| 1.0205 | 3.0 | 111 | 1.1073 | 0.8929 | 0.8931 | 0.8925 | 6.6507 | 16 | 2 | 10.7057 | 1.6016 |
| 0.8912 | 4.0 | 148 | 1.0787 | 0.8967 | 0.8966 | 0.8962 | 6.5896 | 16 | 2 | 10.5926 | 1.6016 |
| 0.8027 | 5.0 | 185 | 1.1123 | 0.8991 | 0.8959 | 0.897 | 6.3994 | 16 | 2 | 10.4164 | 1.1011 |
| 0.7251 | 6.0 | 222 | 1.1148 | 0.8983 | 0.8941 | 0.8957 | 6.3013 | 16 | 2 | 10.3333 | 1.3013 |
| 0.6534 | 7.0 | 259 | 1.1348 | 0.8993 | 0.8931 | 0.8957 | 6.2332 | 16 | 2 | 10.2012 | 1.2012 |
| 0.5895 | 8.0 | 296 | 1.1537 | 0.8982 | 0.8959 | 0.8966 | 6.4945 | 16 | 2 | 10.4995 | 1.6016 |
| 0.5483 | 9.0 | 333 | 1.1656 | 0.901 | 0.8978 | 0.899 | 6.4184 | 16 | 2 | 10.4505 | 1.7017 |
| 0.5117 | 10.0 | 370 | 1.1919 | 0.8977 | 0.896 | 0.8964 | 6.4565 | 15 | 2 | 10.5696 | 1.1011 |
| 0.4639 | 11.0 | 407 | 1.2106 | 0.8999 | 0.8956 | 0.8973 | 6.2653 | 15 | 2 | 10.2943 | 1.001 |
| 0.4267 | 12.0 | 444 | 1.2419 | 0.8975 | 0.8958 | 0.8962 | 6.4625 | 17 | 2 | 10.5115 | 1.7017 |
| 0.4069 | 13.0 | 481 | 1.2583 | 0.9023 | 0.8964 | 0.8988 | 6.1812 | 15 | 2 | 10.1942 | 0.9009 |
| 0.3775 | 14.0 | 518 | 1.2887 | 0.8991 | 0.8982 | 0.8982 | 6.4384 | 15 | 2 | 10.5676 | 1.5015 |
| 0.3495 | 15.0 | 555 | 1.3282 | 0.9015 | 0.8984 | 0.8995 | 6.3604 | 15 | 2 | 10.4895 | 0.9009 |
| 0.3281 | 16.0 | 592 | 1.3276 | 0.9012 | 0.8973 | 0.8988 | 6.2753 | 15 | 2 | 10.3413 | 0.5005 |
| 0.3083 | 17.0 | 629 | 1.3539 | 0.9007 | 0.8979 | 0.8989 | 6.3504 | 16 | 2 | 10.3874 | 1.6016 |
| 0.2906 | 18.0 | 666 | 1.3720 | 0.9006 | 0.8986 | 0.8992 | 6.4204 | 14 | 2 | 10.4785 | 1.2012 |
| 0.2793 | 19.0 | 703 | 1.4130 | 0.8997 | 0.8986 | 0.8987 | 6.4374 | 16 | 2 | 10.5345 | 1.5015 |
| 0.2656 | 20.0 | 740 | 1.4376 | 0.9026 | 0.8986 | 0.9002 | 6.2843 | 16 | 2 | 10.3834 | 1.2012 |
| 0.2399 | 21.0 | 777 | 1.4429 | 0.901 | 0.8997 | 0.8999 | 6.4545 | 16 | 2 | 10.5516 | 1.5015 |
| 0.2316 | 22.0 | 814 | 1.4807 | 0.899 | 0.8987 | 0.8983 | 6.4975 | 16 | 2 | 10.6667 | 1.3013 |
| 0.2237 | 23.0 | 851 | 1.4941 | 0.9002 | 0.8974 | 0.8983 | 6.3363 | 15 | 2 | 10.4484 | 0.9009 |
| 0.2079 | 24.0 | 888 | 1.5101 | 0.9011 | 0.8982 | 0.8992 | 6.3443 | 16 | 2 | 10.4104 | 1.2012 |
| 0.2007 | 25.0 | 925 | 1.5176 | 0.8991 | 0.8983 | 0.8982 | 6.5065 | 16 | 2 | 10.6216 | 1.001 |
| 0.1952 | 26.0 | 962 | 1.5253 | 0.9005 | 0.8979 | 0.8987 | 6.3934 | 15 | 2 | 10.4835 | 1.1011 |
| 0.1901 | 27.0 | 999 | 1.5440 | 0.9007 | 0.8985 | 0.8991 | 6.3904 | 16 | 2 | 10.5185 | 0.8008 |
| 0.1838 | 28.0 | 1036 | 1.5540 | 0.9008 | 0.9002 | 0.9 | 6.4985 | 16 | 2 | 10.6176 | 1.3013 |
| 0.1773 | 29.0 | 1073 | 1.5576 | 0.9013 | 0.9001 | 0.9003 | 6.4835 | 16 | 2 | 10.5866 | 1.3013 |
| 0.1692 | 30.0 | 1110 | 1.5746 | 0.9012 | 0.9003 | 0.9003 | 6.4895 | 16 | 2 | 10.6176 | 1.5015 |
| 0.163 | 31.0 | 1147 | 1.5844 | 0.9014 | 0.9 | 0.9002 | 6.4655 | 16 | 2 | 10.5756 | 1.3013 |
| 0.1587 | 32.0 | 1184 | 1.6071 | 0.9008 | 0.8997 | 0.8998 | 6.4615 | 16 | 2 | 10.6076 | 0.9009 |
| 0.156 | 33.0 | 1221 | 1.6166 | 0.9006 | 0.8998 | 0.8997 | 6.4945 | 16 | 2 | 10.6166 | 1.2012 |
| 0.1546 | 34.0 | 1258 | 1.6099 | 0.9011 | 0.8987 | 0.8994 | 6.3834 | 13 | 2 | 10.4965 | 0.9009 |
| 0.1472 | 35.0 | 1295 | 1.6167 | 0.9018 | 0.8992 | 0.9001 | 6.3974 | 14 | 2 | 10.4665 | 1.001 |
| 0.1472 | 36.0 | 1332 | 1.6271 | 0.9006 | 0.9 | 0.8998 | 6.5185 | 16 | 2 | 10.6216 | 1.5015 |
| 0.1452 | 37.0 | 1369 | 1.6226 | 0.9023 | 0.9007 | 0.901 | 6.4595 | 16 | 2 | 10.5485 | 1.4014 |
| 0.1415 | 38.0 | 1406 | 1.6221 | 0.9015 | 0.9006 | 0.9006 | 6.5005 | 16 | 2 | 10.5846 | 1.4014 |
| 0.1398 | 39.0 | 1443 | 1.6272 | 0.9012 | 0.9002 | 0.9003 | 6.5025 | 16 | 2 | 10.5866 | 1.2012 |
| 0.14 | 40.0 | 1480 | 1.6295 | 0.9015 | 0.9003 | 0.9004 | 6.4845 | 16 | 2 | 10.5656 | 1.1011 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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