File size: 2,913 Bytes
4a1debe fe4fbae |
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 85 86 87 88 89 90 |
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: multinews_model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: multi_news
type: multi_news
config: default
split: test
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.1482
---
<!-- 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. -->
# multinews_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7165
- Rouge1: 0.1482
- Rouge2: 0.0472
- Rougel: 0.1132
- Rougelsum: 0.1132
- Gen Len: 19.0
## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 450 | 2.8616 | 0.1388 | 0.0418 | 0.1057 | 0.1056 | 19.0 |
| 3.2544 | 2.0 | 900 | 2.7991 | 0.1427 | 0.0438 | 0.1089 | 0.1089 | 19.0 |
| 2.999 | 3.0 | 1350 | 2.7693 | 0.1449 | 0.046 | 0.1115 | 0.1114 | 19.0 |
| 2.958 | 4.0 | 1800 | 2.7531 | 0.1466 | 0.0462 | 0.112 | 0.1118 | 19.0 |
| 2.9198 | 5.0 | 2250 | 2.7431 | 0.1466 | 0.0465 | 0.112 | 0.1119 | 19.0 |
| 2.8838 | 6.0 | 2700 | 2.7328 | 0.1474 | 0.0461 | 0.1125 | 0.1123 | 19.0 |
| 2.8774 | 7.0 | 3150 | 2.7270 | 0.1477 | 0.0463 | 0.1126 | 0.1124 | 19.0 |
| 2.8712 | 8.0 | 3600 | 2.7226 | 0.148 | 0.0466 | 0.1128 | 0.1127 | 19.0 |
| 2.854 | 9.0 | 4050 | 2.7197 | 0.1479 | 0.047 | 0.1129 | 0.1128 | 19.0 |
| 2.8541 | 10.0 | 4500 | 2.7188 | 0.1485 | 0.0471 | 0.113 | 0.1129 | 19.0 |
| 2.8541 | 11.0 | 4950 | 2.7168 | 0.1483 | 0.0472 | 0.1131 | 0.1131 | 19.0 |
| 2.8466 | 12.0 | 5400 | 2.7165 | 0.1482 | 0.0472 | 0.1132 | 0.1132 | 19.0 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3 |