flan-t5-base-finetuned-QLoRA-v2
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: 1.0254
- Rouge1: 0.244
- Rouge2: 0.111
- Rougel: 0.2032
- Rougelsum: 0.2292
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|
| 3.0551 | 1.0 | 500 | 2.2941 | 0.2336 | 0.1092 | 0.1969 | 0.217 |
| 1.6422 | 2.0 | 1000 | 1.1665 | 0.2459 | 0.1088 | 0.1991 | 0.227 |
| 1.4067 | 3.0 | 1500 | 1.0762 | 0.2462 | 0.1089 | 0.1982 | 0.2296 |
| 1.2856 | 4.0 | 2000 | 1.0518 | 0.2448 | 0.1112 | 0.2036 | 0.2298 |
| 1.3478 | 5.0 | 2500 | 1.0393 | 0.2458 | 0.1125 | 0.2056 | 0.2303 |
| 1.2114 | 6.0 | 3000 | 1.0340 | 0.2497 | 0.1145 | 0.2084 | 0.2333 |
| 1.3311 | 7.0 | 3500 | 1.0298 | 0.2479 | 0.1143 | 0.207 | 0.233 |
| 1.3081 | 8.0 | 4000 | 1.0270 | 0.2448 | 0.1112 | 0.2035 | 0.2301 |
| 1.1794 | 9.0 | 4500 | 1.0258 | 0.2449 | 0.1112 | 0.2036 | 0.2301 |
| 1.2407 | 10.0 | 5000 | 1.0254 | 0.244 | 0.111 | 0.2032 | 0.2292 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1