metadata
			license: apache-2.0
base_model: google/flan-t5-small
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: flan-t5-small-samsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: test
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 42.6
flan-t5-small-samsum
This model is a fine-tuned version of google/flan-t5-small on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.6729
 - Rouge1: 42.6
 - Rouge2: 18.7153
 - Rougel: 35.4138
 - Rougelsum: 38.8543
 - Gen Len: 16.9170
 
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: 5e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 2
 - mixed_precision_training: Native AMP
 
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | 
|---|---|---|---|---|---|---|---|---|
| 1.8863 | 0.22 | 100 | 1.7049 | 42.0859 | 18.0002 | 34.7349 | 38.3446 | 16.5788 | 
| 1.8463 | 0.43 | 200 | 1.6947 | 42.4056 | 18.3005 | 34.9821 | 38.8013 | 17.3614 | 
| 1.8548 | 0.65 | 300 | 1.6792 | 42.585 | 18.5643 | 35.2235 | 38.8298 | 17.1514 | 
| 1.8358 | 0.87 | 400 | 1.6772 | 42.1544 | 18.2303 | 34.8971 | 38.3609 | 16.5873 | 
| 1.8129 | 1.08 | 500 | 1.6729 | 42.6 | 18.7153 | 35.4138 | 38.8543 | 16.9170 | 
| 1.8068 | 1.3 | 600 | 1.6709 | 42.5217 | 18.3285 | 35.1455 | 38.5954 | 16.9451 | 
| 1.7973 | 1.52 | 700 | 1.6687 | 42.8667 | 18.624 | 35.3429 | 38.9322 | 16.7546 | 
| 1.7979 | 1.74 | 800 | 1.6668 | 42.919 | 18.7388 | 35.4528 | 39.0561 | 16.8791 | 
| 1.7899 | 1.95 | 900 | 1.6670 | 43.0931 | 18.741 | 35.5047 | 39.2321 | 16.9109 | 
Framework versions
- Transformers 4.36.0
 - Pytorch 2.0.0
 - Datasets 2.15.0
 - Tokenizers 0.15.0