metadata
license: other
base_model: north/t5_large_NCC_modern
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: North-T5-large_NO-QA-idun-20epoch
results: []
North-T5-large_NO-QA-idun-20epoch
This model is a fine-tuned version of north/t5_large_NCC_modern on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5362
- Rouge1: 38.769
- Rouge2: 15.9471
- Rougel: 26.5124
- Rougelsum: 34.9947
- Gen Len: 94.6489
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 0.98 | 46 | 4.5352 | 17.0492 | 4.4759 | 10.456 | 15.2577 | 118.1702 |
| No log | 1.99 | 93 | 1.9786 | 31.9727 | 10.2837 | 18.7297 | 28.8476 | 82.0426 |
| No log | 2.99 | 140 | 1.6381 | 33.0332 | 11.5675 | 20.361 | 29.3026 | 74.0 |
| No log | 4.0 | 187 | 1.5769 | 35.8586 | 13.2608 | 23.5819 | 32.6021 | 90.3298 |
| No log | 4.98 | 233 | 1.5411 | 37.644 | 14.5558 | 24.9032 | 33.9629 | 94.6702 |
| No log | 5.99 | 280 | 1.5349 | 36.9237 | 14.2153 | 24.9174 | 33.2155 | 85.8404 |
| No log | 6.99 | 327 | 1.5120 | 38.1967 | 15.2791 | 25.5664 | 34.4922 | 92.9362 |
| No log | 8.0 | 374 | 1.5094 | 38.8448 | 15.6077 | 26.2711 | 34.9747 | 93.0851 |
| No log | 8.98 | 420 | 1.5133 | 38.0596 | 15.1036 | 26.38 | 34.2785 | 90.2021 |
| No log | 9.99 | 467 | 1.5221 | 38.465 | 14.8936 | 26.014 | 34.6291 | 97.8085 |
| 2.5538 | 10.99 | 514 | 1.5207 | 39.806 | 16.0433 | 27.2048 | 35.8647 | 97.9149 |
| 2.5538 | 12.0 | 561 | 1.5194 | 38.1513 | 15.4085 | 26.1441 | 34.4682 | 88.4787 |
| 2.5538 | 12.98 | 607 | 1.5199 | 38.2157 | 15.363 | 26.0975 | 34.5609 | 94.9043 |
| 2.5538 | 13.99 | 654 | 1.5243 | 38.6499 | 15.4096 | 25.9533 | 34.6419 | 94.0638 |
| 2.5538 | 14.99 | 701 | 1.5297 | 38.1416 | 15.1179 | 26.139 | 34.6999 | 93.7447 |
| 2.5538 | 16.0 | 748 | 1.5320 | 38.6153 | 15.6661 | 26.3465 | 34.9576 | 95.7979 |
| 2.5538 | 16.98 | 794 | 1.5318 | 38.0022 | 15.5531 | 25.9628 | 34.2994 | 93.3936 |
| 2.5538 | 17.99 | 841 | 1.5364 | 37.9608 | 15.396 | 25.7531 | 34.3565 | 92.2553 |
| 2.5538 | 18.99 | 888 | 1.5352 | 38.9808 | 16.235 | 26.7723 | 35.2738 | 95.3085 |
| 2.5538 | 19.68 | 920 | 1.5362 | 38.769 | 15.9471 | 26.5124 | 34.9947 | 94.6489 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.3.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2