File size: 2,398 Bytes
254a95c |
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 |
---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-base-finetuned-scope-summarization
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. -->
# flan-t5-base-finetuned-scope-summarization
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co./google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2068
- Rouge1: 21.1277
- Rouge2: 12.8385
- Rougel: 19.2508
- Rougelsum: 19.1904
## 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: 5.6e-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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.7131 | 1.0 | 40 | 0.3103 | 13.5236 | 5.6576 | 11.5554 | 11.5235 |
| 0.3577 | 2.0 | 80 | 0.2444 | 20.2029 | 12.8573 | 18.8596 | 18.7919 |
| 0.3116 | 3.0 | 120 | 0.2315 | 20.1102 | 12.5261 | 18.5794 | 18.6565 |
| 0.3041 | 4.0 | 160 | 0.2235 | 19.7317 | 12.0446 | 18.1138 | 18.1158 |
| 0.2856 | 5.0 | 200 | 0.2166 | 19.9465 | 12.3127 | 18.2483 | 18.1644 |
| 0.2972 | 6.0 | 240 | 0.2128 | 20.5461 | 12.4766 | 18.5225 | 18.5724 |
| 0.2787 | 7.0 | 280 | 0.2101 | 20.383 | 12.8677 | 19.021 | 18.9993 |
| 0.2837 | 8.0 | 320 | 0.2087 | 21.0603 | 12.7582 | 19.2214 | 19.1966 |
| 0.2803 | 9.0 | 360 | 0.2074 | 20.9823 | 12.7617 | 19.1207 | 19.0656 |
| 0.2696 | 10.0 | 400 | 0.2068 | 21.1277 | 12.8385 | 19.2508 | 19.1904 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|