license: apache-2.0 | |
tags: | |
- generated_from_trainer | |
datasets: | |
- billsum | |
metrics: | |
- rouge | |
base_model: t5-small | |
model-index: | |
- name: search_summarize_v1 | |
results: | |
- task: | |
type: text2text-generation | |
name: Sequence-to-sequence Language Modeling | |
dataset: | |
name: billsum | |
type: billsum | |
config: default | |
split: ca_test | |
args: default | |
metrics: | |
- type: rouge | |
value: 0.1476 | |
name: Rouge1 | |
<!-- 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. --> | |
# search_summarize_v1 | |
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: 2.5224 | |
- Rouge1: 0.1476 | |
- Rouge2: 0.0551 | |
- Rougel: 0.1228 | |
- Rougelsum: 0.1228 | |
- 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: 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 | 62 | 2.8176 | 0.1281 | 0.0401 | 0.1087 | 0.1086 | 19.0 | | |
| No log | 2.0 | 124 | 2.5989 | 0.1372 | 0.0476 | 0.1138 | 0.1137 | 19.0 | | |
| No log | 3.0 | 186 | 2.5386 | 0.1464 | 0.0541 | 0.1218 | 0.1219 | 19.0 | | |
| No log | 4.0 | 248 | 2.5224 | 0.1476 | 0.0551 | 0.1228 | 0.1228 | 19.0 | | |
### Framework versions | |
- Transformers 4.28.1 | |
- Pytorch 2.0.0+cu118 | |
- Datasets 2.12.0 | |
- Tokenizers 0.13.3 | |