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bigData_w9
This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0525
- Bleu4: 0.1309
- Rouge1: 0.4023
- Rouge2: 0.1845
- Rougel: 0.2757
- Rougelsum: 0.2753
- Gen Len: 76.4341
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: 32
- eval_batch_size: 32
- seed: 516
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu4 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|---|
| 2.0178 | 0.45 | 100 | 1.4840 | 0.1337 | 0.3875 | 0.1805 | 0.2688 | 0.2689 | 67.5509 |
| 1.142 | 0.89 | 200 | 1.1196 | 0.1296 | 0.3897 | 0.1766 | 0.2669 | 0.2667 | 69.3817 |
| 1.0693 | 1.34 | 300 | 1.0796 | 0.1345 | 0.3951 | 0.1818 | 0.2727 | 0.2727 | 70.015 |
| 1.0536 | 1.78 | 400 | 1.0684 | 0.1284 | 0.399 | 0.1839 | 0.2731 | 0.2729 | 77.3069 |
| 1.0084 | 2.23 | 500 | 1.0624 | 0.1287 | 0.3977 | 0.1808 | 0.2729 | 0.2729 | 76.7904 |
| 0.9855 | 2.67 | 600 | 1.0575 | 0.1349 | 0.4005 | 0.1843 | 0.2789 | 0.2787 | 72.4521 |
| 0.9812 | 3.12 | 700 | 1.0568 | 0.1303 | 0.4009 | 0.1847 | 0.2756 | 0.2752 | 76.1781 |
| 0.9916 | 3.56 | 800 | 1.0507 | 0.1364 | 0.4014 | 0.1853 | 0.279 | 0.2789 | 72.9746 |
| 0.9856 | 4.01 | 900 | 1.0507 | 0.1327 | 0.4003 | 0.1833 | 0.276 | 0.2758 | 74.9461 |
| 0.9747 | 4.45 | 1000 | 1.0519 | 0.1328 | 0.4014 | 0.185 | 0.276 | 0.2757 | 75.9461 |
| 0.9519 | 4.9 | 1100 | 1.0525 | 0.1309 | 0.4023 | 0.1845 | 0.2757 | 0.2753 | 76.4341 |
Framework versions
- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
