File size: 2,492 Bytes
1b63220 |
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 |
---
license: apache-2.0
library_name: peft
tags:
- summarization
- generated_from_trainer
datasets:
- gov_report_summarization_dataset
metrics:
- rouge
base_model: google/flan-t5-base
model-index:
- name: flan-t5-base-finetuned-govReport-3072
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-govReport-3072
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the gov_report_summarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.042
- Rouge2: 0.0216
- Rougel: 0.0379
- Rougelsum: 0.0406
## 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: 3e-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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 0.0 | 1.0 | 250 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 2.0 | 500 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 3.0 | 750 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 4.0 | 1000 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 5.0 | 1250 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 6.0 | 1500 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 7.0 | 1750 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 8.0 | 2000 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 9.0 | 2250 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
| 0.0 | 10.0 | 2500 | nan | 0.042 | 0.0216 | 0.0379 | 0.0406 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1 |