metadata
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: finetuned_t5_summarize
results: []
finetuned_t5_summarize
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2034
- Rouge1: 0.8046
- Rouge2: 0.7768
- Rougel: 0.8018
- Rougelsum: 0.8018
- Gen Len: 16.8404
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 | 301 | 0.2652 | 0.7765 | 0.7432 | 0.7726 | 0.7728 | 16.7722 |
| 0.3923 | 2.0 | 602 | 0.2248 | 0.7967 | 0.768 | 0.7944 | 0.7943 | 16.7797 |
| 0.3923 | 3.0 | 903 | 0.2074 | 0.8027 | 0.775 | 0.7997 | 0.7996 | 16.8105 |
| 0.2356 | 4.0 | 1204 | 0.2034 | 0.8046 | 0.7768 | 0.8018 | 0.8018 | 16.8404 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2