File size: 2,229 Bytes
1ea28f2 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: flan-t5-small-samsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: test
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 43.7829
---
<!-- 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-small-samsum
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6325
- Rouge1: 43.7829
- Rouge2: 19.4994
- Rougel: 36.5484
- Rougelsum: 39.9323
- Gen Len: 16.8730
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.8137 | 1.0 | 1842 | 1.6636 | 42.6155 | 18.9113 | 35.7997 | 39.046 | 16.7473 |
| 1.7502 | 2.0 | 3684 | 1.6408 | 43.3833 | 19.1709 | 36.0178 | 39.5973 | 16.8620 |
| 1.6864 | 3.0 | 5526 | 1.6372 | 43.31 | 19.2269 | 35.9239 | 39.6082 | 16.8559 |
| 1.6647 | 4.0 | 7368 | 1.6334 | 43.7043 | 19.462 | 36.4417 | 39.8969 | 16.9512 |
| 1.6391 | 5.0 | 9210 | 1.6325 | 43.7829 | 19.4994 | 36.5484 | 39.9323 | 16.8730 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.2
|