metadata
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: SummarEaseElementaryV2
results: []
SummarEaseElementaryV2
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3269
- Rouge1: 0.1335
- Rouge2: 0.0509
- Rougel: 0.1066
- Rougelsum: 0.1075
- Gen Len: 20.0
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 2.3970 | 0.0914 | 0.0227 | 0.0746 | 0.0745 | 20.0 |
| No log | 2.0 | 2 | 2.3609 | 0.1195 | 0.0397 | 0.0957 | 0.0962 | 20.0 |
| No log | 3.0 | 3 | 2.3386 | 0.1323 | 0.0496 | 0.1066 | 0.1075 | 20.0 |
| No log | 4.0 | 4 | 2.3269 | 0.1335 | 0.0509 | 0.1066 | 0.1075 | 20.0 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1