flan-t5-base-finetuned-QLoRA-10000
This model is a fine-tuned version of google/flan-t5-base on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 1.0625
- Rouge1: 0.2397
- Rouge2: 0.1107
- Rougel: 0.1948
- Rougelsum: 0.226
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: 3e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.3695 | 1.0 | 1250 | 1.1374 | 0.232 | 0.1046 | 0.1884 | 0.218 |
| 1.197 | 2.0 | 2500 | 1.0885 | 0.2371 | 0.1093 | 0.1934 | 0.2236 |
| 1.1489 | 3.0 | 3750 | 1.0765 | 0.2389 | 0.1098 | 0.1939 | 0.2248 |
| 1.156 | 4.0 | 5000 | 1.0693 | 0.2403 | 0.1107 | 0.195 | 0.226 |
| 1.1135 | 5.0 | 6250 | 1.0663 | 0.2393 | 0.1102 | 0.1944 | 0.2252 |
| 1.1607 | 6.0 | 7500 | 1.0648 | 0.24 | 0.1109 | 0.1951 | 0.2259 |
| 1.1222 | 7.0 | 8750 | 1.0635 | 0.2398 | 0.1106 | 0.1947 | 0.2256 |
| 1.1619 | 8.0 | 10000 | 1.0629 | 0.2399 | 0.1106 | 0.1949 | 0.2259 |
| 1.1366 | 9.0 | 11250 | 1.0626 | 0.2397 | 0.1108 | 0.1948 | 0.226 |
| 1.2062 | 10.0 | 12500 | 1.0625 | 0.2397 | 0.1107 | 0.1948 | 0.226 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1