metadata
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
model-index:
- name: text_shortening_model_v80
results: []
text_shortening_model_v80
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1772
- Bert precision: 0.8996
- Bert recall: 0.9009
- Bert f1-score: 0.8998
- Average word count: 6.8393
- Max word count: 16
- Min word count: 3
- Average token count: 11.092
- % shortened texts with length > 12: 0.9816
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: 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: 25
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.3549 | 1.0 | 30 | 1.0184 | 0.8861 | 0.887 | 0.886 | 7.016 | 18 | 2 | 11.2061 | 2.6994 |
| 0.9772 | 2.0 | 60 | 0.9395 | 0.889 | 0.8903 | 0.8892 | 6.9436 | 16 | 2 | 11.1276 | 1.8405 |
| 0.8398 | 3.0 | 90 | 0.9211 | 0.8904 | 0.8916 | 0.8906 | 6.9534 | 16 | 2 | 11.119 | 2.3313 |
| 0.7412 | 4.0 | 120 | 0.9235 | 0.8926 | 0.8945 | 0.8931 | 6.9239 | 16 | 2 | 11.1926 | 1.5951 |
| 0.6652 | 5.0 | 150 | 0.9173 | 0.8936 | 0.8968 | 0.8947 | 7.0442 | 16 | 3 | 11.4135 | 1.5951 |
| 0.5992 | 6.0 | 180 | 0.9270 | 0.8962 | 0.8982 | 0.8968 | 6.9485 | 16 | 3 | 11.2209 | 1.8405 |
| 0.5381 | 7.0 | 210 | 0.9565 | 0.8948 | 0.8962 | 0.8951 | 6.8209 | 16 | 2 | 11.1043 | 1.3497 |
| 0.4899 | 8.0 | 240 | 0.9812 | 0.8956 | 0.8984 | 0.8966 | 7.0098 | 16 | 2 | 11.2282 | 1.9632 |
| 0.4528 | 9.0 | 270 | 0.9842 | 0.8954 | 0.8979 | 0.8962 | 6.9791 | 16 | 3 | 11.2773 | 1.7178 |
| 0.4233 | 10.0 | 300 | 1.0057 | 0.897 | 0.8977 | 0.8969 | 6.8294 | 16 | 2 | 11.0589 | 1.5951 |
| 0.3971 | 11.0 | 330 | 1.0276 | 0.8967 | 0.8976 | 0.8967 | 6.8761 | 16 | 2 | 11.1411 | 1.1043 |
| 0.3713 | 12.0 | 360 | 1.0316 | 0.8962 | 0.8958 | 0.8955 | 6.7583 | 16 | 2 | 10.9816 | 1.1043 |
| 0.3428 | 13.0 | 390 | 1.0775 | 0.898 | 0.8982 | 0.8977 | 6.838 | 16 | 2 | 11.092 | 1.1043 |
| 0.3256 | 14.0 | 420 | 1.0831 | 0.8987 | 0.8993 | 0.8985 | 6.8552 | 16 | 2 | 11.1141 | 1.227 |
| 0.3116 | 15.0 | 450 | 1.0982 | 0.8979 | 0.899 | 0.898 | 6.8638 | 16 | 2 | 11.119 | 1.1043 |
| 0.2958 | 16.0 | 480 | 1.1273 | 0.8965 | 0.8991 | 0.8974 | 6.9546 | 16 | 3 | 11.238 | 1.5951 |
| 0.2838 | 17.0 | 510 | 1.1205 | 0.8984 | 0.9003 | 0.8989 | 6.9583 | 16 | 3 | 11.227 | 1.4724 |
| 0.2683 | 18.0 | 540 | 1.1435 | 0.8978 | 0.8991 | 0.898 | 6.8847 | 16 | 2 | 11.1178 | 1.227 |
| 0.2594 | 19.0 | 570 | 1.1495 | 0.899 | 0.8986 | 0.8983 | 6.7939 | 16 | 2 | 11.0307 | 0.8589 |
| 0.2522 | 20.0 | 600 | 1.1621 | 0.8993 | 0.8992 | 0.8988 | 6.7767 | 16 | 3 | 11.0294 | 0.7362 |
| 0.2457 | 21.0 | 630 | 1.1693 | 0.8991 | 0.9017 | 0.9 | 6.9006 | 16 | 3 | 11.2 | 0.9816 |
| 0.2442 | 22.0 | 660 | 1.1728 | 0.8986 | 0.9008 | 0.8992 | 6.8773 | 16 | 3 | 11.1644 | 0.9816 |
| 0.235 | 23.0 | 690 | 1.1740 | 0.8986 | 0.9002 | 0.899 | 6.8564 | 16 | 3 | 11.1178 | 0.9816 |
| 0.2319 | 24.0 | 720 | 1.1751 | 0.8995 | 0.9008 | 0.8997 | 6.8417 | 16 | 3 | 11.0908 | 0.9816 |
| 0.2315 | 25.0 | 750 | 1.1772 | 0.8996 | 0.9009 | 0.8998 | 6.8393 | 16 | 3 | 11.092 | 0.9816 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3