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t5-large-finetuned-break-qdmr-decomposition
This model is a fine-tuned version of t5-large on the break_data dataset. It achieves the following results on the evaluation set:
- Loss: 0.1729
- Bleu: 0.2217
- Brevity Penalty: 0.2926
- Length Ratio: 0.4487
- Translation Length: 108954
- Reference Length: 242845
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 128
- 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 | Bleu | Brevity Penalty | Length Ratio | Translation Length | Reference Length |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 346 | 0.2217 | 0.2190 | 0.2973 | 0.4519 | 109738 | 242845 |
| 0.3597 | 2.0 | 692 | 0.1898 | 0.2213 | 0.2944 | 0.4499 | 109245 | 242845 |
| 0.1943 | 3.0 | 1038 | 0.1780 | 0.2213 | 0.2936 | 0.4494 | 109125 | 242845 |
| 0.1943 | 4.0 | 1385 | 0.1722 | 0.2209 | 0.2926 | 0.4486 | 108943 | 242845 |
| 0.1588 | 5.0 | 1731 | 0.1708 | 0.2221 | 0.2938 | 0.4495 | 109159 | 242845 |
| 0.1395 | 6.0 | 2077 | 0.1699 | 0.2209 | 0.2907 | 0.4473 | 108635 | 242845 |
| 0.1395 | 7.0 | 2423 | 0.1699 | 0.2219 | 0.2927 | 0.4487 | 108964 | 242845 |
| 0.1245 | 8.0 | 2770 | 0.1717 | 0.2215 | 0.2924 | 0.4485 | 108909 | 242845 |
| 0.1152 | 9.0 | 3116 | 0.1724 | 0.2215 | 0.2924 | 0.4485 | 108914 | 242845 |
| 0.1152 | 9.99 | 3460 | 0.1729 | 0.2217 | 0.2926 | 0.4487 | 108954 | 242845 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
