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final-3.0-t5-base-2023-06-20_13-18
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0913
- Gen Len: 19.0
- Bertscorer-p: 0.5070
- Bertscorer-r: 0.0536
- Bertscorer-f1: 0.2705
- Sacrebleu-score: 4.7246
- Sacrebleu-precisions: [82.26851609027145, 72.56818398298178, 64.03031654034775, 58.101657218801705]
- Bleu-bp: 0.0688
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: 0.0003
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Gen Len | Bertscorer-p | Bertscorer-r | Bertscorer-f1 | Sacrebleu-score | Sacrebleu-precisions | Bleu-bp |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.137 | 1.0 | 10382 | 0.1146 | 19.0 | 0.4908 | 0.0444 | 0.2581 | 3.8066 | [81.64981564768446, 70.67489114658926, 61.40689811921132, 54.44849682509699] | 0.0574 |
| 0.0937 | 2.0 | 20764 | 0.0913 | 19.0 | 0.5070 | 0.0536 | 0.2705 | 4.7246 | [82.26851609027145, 72.56818398298178, 64.03031654034775, 58.101657218801705] | 0.0688 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
