|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: google-t5/t5-large |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- generator |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: summarise_cy |
|
|
results: |
|
|
- task: |
|
|
name: Sequence-to-sequence Language Modeling |
|
|
type: text2text-generation |
|
|
dataset: |
|
|
name: generator |
|
|
type: generator |
|
|
config: default |
|
|
split: train |
|
|
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. --> |
|
|
|
|
|
# summarise_cy |
|
|
|
|
|
This model is a fine-tuned version of [google-t5/t5-large](https://huggingface.co/google-t5/t5-large) on the generator dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: nan |
|
|
- Rouge1: 0.1434 |
|
|
- Rouge2: 0.0535 |
|
|
- Rougel: 0.1286 |
|
|
- Rougelsum: 0.1287 |
|
|
- Gen Len: 20.0 |
|
|
|
|
|
## 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: 1 |
|
|
- eval_batch_size: 1 |
|
|
- seed: 42 |
|
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 10 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
|
| No log | 1.0 | 410 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 2.0 | 820 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 3.0 | 1230 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 4.0 | 1640 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 5.0 | 2050 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 6.0 | 2460 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 7.0 | 2870 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 8.0 | 3280 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 9.0 | 3690 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
| 0.0 | 10.0 | 4100 | nan | 0.1434 | 0.0535 | 0.1286 | 0.1287 | 20.0 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.52.4 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.6.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
