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speller-t5-finetuned
summervent/speller-t5-finetuned
speller-t5-finetuned is a machine learning model from summervent. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- t5
- Access
- Public
- Created
- Jan 31, 2023
- Updated
- Jan 31, 2023
- SHA
- c27ef255
Model card
From the Hugging Face model README
<!-- 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. -->
speller-t5-finetuned
This model is a fine-tuned version of UrukHan/t5-russian-spell on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0737
- Rouge1: 25.3988
- Rouge2: 11.756
- Rougel: 25.051
- Rougelsum: 25.2041
- Gen Len: 41.3929
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.1861 | 0.07 | 1000 | 0.1074 | 24.351 | 9.9107 | 24.0512 | 24.1443 | 41.4375 |
| 0.1629 | 0.14 | 2000 | 0.0918 | 25.1414 | 11.3393 | 24.8541 | 24.9175 | 41.3839 |
| 0.1545 | 0.21 | 3000 | 0.0898 | 25.2909 | 11.5882 | 24.981 | 25.0772 | 41.2857 |
| 0.1507 | 0.29 | 4000 | 0.0860 | 25.1414 | 11.3393 | 24.8541 | 24.9175 | 41.3571 |
| 0.1472 | 0.36 | 5000 | 0.0823 | 25.2909 | 11.5882 | 24.981 | 25.0772 | 41.3661 |
| 0.1417 | 0.43 | 6000 | 0.0794 | 24.6565 | 10.2976 | 24.265 | 24.4006 | 41.4107 |
| 0.1411 | 0.5 | 7000 | 0.0788 | 25.1414 | 11.3393 | 24.8541 | 24.9175 | 41.3482 |
| 0.1395 | 0.57 | 8000 | 0.0786 | 25.2909 | 11.5882 | 24.981 | 25.0772 | 41.3125 |
| 0.1318 | 0.64 | 9000 | 0.0774 | 25.2909 | 11.5882 | 24.981 | 25.0772 | 41.3929 |
| 0.1336 | 0.72 | 10000 | 0.0758 | 25.2394 | 11.5476 | 24.9777 | 25.0511 | 41.3839 |
| 0.1332 | 0.79 | 11000 | 0.0743 | 25.2394 | 11.5476 | 24.9777 | 25.0511 | 41.3482 |
| 0.1309 | 0.86 | 12000 | 0.0734 | 25.2394 | 11.5476 | 24.9777 | 25.0511 | 41.3393 |
| 0.1264 | 0.93 | 13000 | 0.0737 | 25.3988 | 11.756 | 25.051 | 25.2041 | 41.3929 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Library
- transformers
- Type
- t5
- Created
- Jan 31, 2023
- Updated
- Jan 31, 2023