long-t5-scisumm-accelerate-v2
This model is a fine-tuned version of pszemraj/long-t5-tglobal-base-sci-simplify on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0496
- Rouge1: 39.8436
- Rouge2: 14.763
- Rougel: 25.6676
- Rougelsum: 36.482
- Gen Len: 103.02
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: 4e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.0771 | 0.9868 | 28 | 1.0594 | 39.2592 | 13.6097 | 25.1508 | 35.285 | 111.22 |
1.0193 | 1.9736 | 56 | 1.0530 | 39.1521 | 14.855 | 25.4706 | 35.3713 | 110.14 |
0.9545 | 2.9604 | 84 | 1.0496 | 39.8436 | 14.763 | 25.6676 | 36.482 | 103.02 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.19.1
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