weights
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6183
- Rouge1: 71.4127
- Rouge2: 61.0414
- Rougel: 70.6761
- Rougelsum: 70.696
- Gen Len: 17.3005
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.775 | 0.48 | 500 | 0.6329 | 71.2683 | 60.7856 | 70.5268 | 70.5461 | 17.3119 |
| 0.6892 | 0.96 | 1000 | 0.6183 | 71.4127 | 61.0414 | 70.6761 | 70.696 | 17.3005 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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