metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_first_summarization_model
results: []
my_first_summarization_model
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5001
- Rouge1: 0.1369
- Rouge2: 0.0522
- Rougel: 0.1122
- Rougelsum: 0.1123
- 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: 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: 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 | 2.7763 | 0.1125 | 0.0313 | 0.0938 | 0.0939 | 19.0 |
| No log | 2.0 | 124 | 2.5706 | 0.1291 | 0.0444 | 0.1059 | 0.1062 | 19.0 |
| No log | 3.0 | 186 | 2.5161 | 0.1366 | 0.0516 | 0.1118 | 0.112 | 19.0 |
| No log | 4.0 | 248 | 2.5001 | 0.1369 | 0.0522 | 0.1122 | 0.1123 | 19.0 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3