File size: 2,124 Bytes
f0c577b |
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:
- multi_news
metrics:
- rouge
model-index:
- name: summarizer
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: 0.1434
---
<!-- 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. -->
# summarizer
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: 2.7745
- Rouge1: 0.1434
- Rouge2: 0.0448
- Rougel: 0.1097
- Rougelsum: 0.1097
- Gen Len: 18.9968
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 352 | 2.8572 | 0.1386 | 0.0423 | 0.106 | 0.106 | 18.9968 |
| 3.2016 | 2.0 | 704 | 2.8029 | 0.1415 | 0.0435 | 0.108 | 0.108 | 18.9966 |
| 3.0361 | 3.0 | 1056 | 2.7814 | 0.143 | 0.0446 | 0.1093 | 0.1093 | 18.9968 |
| 3.0361 | 4.0 | 1408 | 2.7745 | 0.1434 | 0.0448 | 0.1097 | 0.1097 | 18.9968 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
|