metadata
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
summarise_cy
This model is a fine-tuned version of 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