File size: 2,327 Bytes
babab83 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
- bleu
model-index:
- name: T5-small_finetuned_billsum_subset_model_bs32_lr0.0001
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: billsum
type: billsum
config: default
split: ca_test
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.191
- name: Bleu
type: bleu
value: 0.0007
---
<!-- 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. -->
# T5-small_finetuned_billsum_subset_model_bs32_lr0.0001
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9700
- Rouge1: 0.191
- Rouge2: 0.0987
- Rougel: 0.1676
- Rougelsum: 0.1673
- Gen Len: 19.0
- Bleu: 0.0007
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Bleu |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|
| No log | 1.0 | 31 | 1.9769 | 0.1885 | 0.0975 | 0.1664 | 0.166 | 19.0 | 0.0008 |
| No log | 2.0 | 62 | 1.9730 | 0.1881 | 0.097 | 0.1643 | 0.1642 | 19.0 | 0.0007 |
| No log | 3.0 | 93 | 1.9753 | 0.1869 | 0.0945 | 0.1644 | 0.1642 | 19.0 | 0.0007 |
| No log | 4.0 | 124 | 1.9700 | 0.191 | 0.0987 | 0.1676 | 0.1673 | 19.0 | 0.0007 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
|