metadata
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-dagbani
results: []
t5-small-dagbani
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: 3.4567
- Rouge1: 2.9794
- Rouge2: 0.0784
- Rougel: 2.9416
- Rougelsum: 3.0119
- Gen Len: 9.5392
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
3.8983 | 1.0 | 455 | 3.6240 | 1.1964 | 0.0 | 1.193 | 1.2108 | 9.7647 |
3.6379 | 2.0 | 910 | 3.5350 | 1.3174 | 0.0 | 1.3085 | 1.3079 | 9.4902 |
3.9076 | 3.0 | 1365 | 3.4915 | 2.1136 | 0.0 | 2.0703 | 2.1291 | 9.5980 |
3.8679 | 4.0 | 1820 | 3.4649 | 2.8498 | 0.0784 | 2.8294 | 2.8802 | 9.5098 |
3.9169 | 5.0 | 2275 | 3.4567 | 2.9794 | 0.0784 | 2.9416 | 3.0119 | 9.5392 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1