metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-policy
results: []
t5-small-finetuned-policy
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6990
- Rouge1: 18.4909
- Rouge2: 10.2538
- Rougel: 15.7923
- Rougelsum: 17.7389
- 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: 8
- eval_batch_size: 8
- 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 | 9 | 3.8135 | 17.7379 | 9.4809 | 15.1302 | 17.2319 | 19.0 |
| No log | 2.0 | 18 | 3.1032 | 18.6526 | 10.4901 | 15.8718 | 17.8287 | 19.0 |
| No log | 3.0 | 27 | 2.7841 | 18.4909 | 10.2538 | 15.7923 | 17.7389 | 19.0 |
| No log | 4.0 | 36 | 2.6990 | 18.4909 | 10.2538 | 15.7923 | 17.7389 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1