File size: 2,540 Bytes
a9b9e2a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-paraphrasing-mlm
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. -->
# t5-small-paraphrasing-mlm
This model is a fine-tuned version of [gayanin/t5-small-paraphrase-pubmed](https://huggingface.co/gayanin/t5-small-paraphrase-pubmed) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7030
- Rouge2 Precision: 0.6576
- Rouge2 Recall: 0.4712
- Rouge2 Fmeasure: 0.532
## 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: 2e-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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.9215 | 1.0 | 13833 | 0.8050 | 0.6352 | 0.454 | 0.5131 |
| 0.855 | 2.0 | 27666 | 0.7679 | 0.6411 | 0.4589 | 0.5184 |
| 0.8387 | 3.0 | 41499 | 0.7464 | 0.6464 | 0.4626 | 0.5226 |
| 0.8267 | 4.0 | 55332 | 0.7315 | 0.6513 | 0.4671 | 0.5273 |
| 0.7879 | 5.0 | 69165 | 0.7217 | 0.6534 | 0.4687 | 0.529 |
| 0.7738 | 6.0 | 82998 | 0.7142 | 0.6548 | 0.4688 | 0.5295 |
| 0.7793 | 7.0 | 96831 | 0.7094 | 0.6553 | 0.4694 | 0.53 |
| 0.7654 | 8.0 | 110664 | 0.7056 | 0.6573 | 0.4704 | 0.5313 |
| 0.7675 | 9.0 | 124497 | 0.7036 | 0.6577 | 0.4712 | 0.532 |
| 0.7662 | 10.0 | 138330 | 0.7030 | 0.6576 | 0.4712 | 0.532 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6
|