File size: 3,465 Bytes
62f0441 |
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 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-flan-t5-20-epochs
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. -->
# fine-tuned-flan-t5-20-epochs
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7842
- Rouge1: 0.2614
- Rouge2: 0.0824
- Rougel: 0.226
- Rougelsum: 0.2273
- Gen Len: 14.54
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 301 | 1.8551 | 0.1314 | 0.0425 | 0.1139 | 0.1139 | 11.4 |
| 2.7128 | 2.0 | 602 | 0.9826 | 0.1868 | 0.065 | 0.1564 | 0.1571 | 15.06 |
| 2.7128 | 3.0 | 903 | 0.8569 | 0.2079 | 0.0718 | 0.1716 | 0.1722 | 15.05 |
| 1.1113 | 4.0 | 1204 | 0.8300 | 0.2141 | 0.0705 | 0.181 | 0.181 | 14.59 |
| 0.9116 | 5.0 | 1505 | 0.8204 | 0.2254 | 0.0837 | 0.1943 | 0.1945 | 14.92 |
| 0.9116 | 6.0 | 1806 | 0.8116 | 0.243 | 0.0807 | 0.2074 | 0.2072 | 15.03 |
| 0.8732 | 7.0 | 2107 | 0.8082 | 0.2376 | 0.0752 | 0.2015 | 0.2016 | 14.83 |
| 0.8732 | 8.0 | 2408 | 0.8007 | 0.2345 | 0.0735 | 0.2015 | 0.2021 | 14.41 |
| 0.8336 | 9.0 | 2709 | 0.7968 | 0.2456 | 0.0757 | 0.2081 | 0.2081 | 14.4 |
| 0.8151 | 10.0 | 3010 | 0.7942 | 0.2544 | 0.0752 | 0.2134 | 0.2146 | 14.58 |
| 0.8151 | 11.0 | 3311 | 0.7924 | 0.2497 | 0.0783 | 0.2118 | 0.2124 | 14.5 |
| 0.8187 | 12.0 | 3612 | 0.7907 | 0.2552 | 0.0769 | 0.2189 | 0.2191 | 14.43 |
| 0.8187 | 13.0 | 3913 | 0.7891 | 0.258 | 0.077 | 0.2197 | 0.2199 | 14.37 |
| 0.8028 | 14.0 | 4214 | 0.7867 | 0.2511 | 0.0801 | 0.2146 | 0.2147 | 14.71 |
| 0.7793 | 15.0 | 4515 | 0.7852 | 0.2551 | 0.0777 | 0.2175 | 0.2177 | 14.67 |
| 0.7793 | 16.0 | 4816 | 0.7858 | 0.2594 | 0.0774 | 0.2219 | 0.2219 | 14.47 |
| 0.7872 | 17.0 | 5117 | 0.7850 | 0.2609 | 0.0803 | 0.2233 | 0.2244 | 14.56 |
| 0.7872 | 18.0 | 5418 | 0.7843 | 0.2599 | 0.0811 | 0.2242 | 0.2256 | 14.55 |
| 0.7756 | 19.0 | 5719 | 0.7844 | 0.261 | 0.0824 | 0.2256 | 0.2271 | 14.55 |
| 0.7752 | 20.0 | 6020 | 0.7842 | 0.2614 | 0.0824 | 0.226 | 0.2273 | 14.54 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
|