LongT5-XLarge-NSPCC
This model is a fine-tuned version of google/long-t5-tglobal-xl on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6802
- Rouge1: 0.522
- Rouge2: 0.2398
- Rougel: 0.3131
- Rougelsum: 0.3134
- Gen Len: 310.4149
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
3.7613 | 0.9960 | 188 | 0.7287 | 0.4625 | 0.1767 | 0.2497 | 0.2491 | 375.9149 |
0.8593 | 1.9974 | 377 | 0.6978 | 0.4823 | 0.2081 | 0.2782 | 0.2781 | 364.7021 |
0.786 | 2.9987 | 566 | 0.6765 | 0.5097 | 0.2262 | 0.2997 | 0.3004 | 320.3298 |
0.7648 | 4.0 | 755 | 0.6783 | 0.5225 | 0.2382 | 0.3115 | 0.3113 | 315.383 |
0.7594 | 4.9801 | 940 | 0.6802 | 0.522 | 0.2398 | 0.3131 | 0.3134 | 310.4149 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for scott156/LongT5XLNSPCCV1
Base model
google/long-t5-tglobal-xl