qm_sum_t5-large
This model is a fine-tuned version of t5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0521
- Rouge2: 0.0088
- Rougel: 0.0464
- Rougelsum: 0.0462
- Gen Len: 19.0
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 | 0.99 | 78 | nan | 0.0521 | 0.0088 | 0.0464 | 0.0462 | 19.0 |
| No log | 1.99 | 157 | nan | 0.0521 | 0.0088 | 0.0464 | 0.0462 | 19.0 |
| No log | 3.0 | 236 | nan | 0.0521 | 0.0088 | 0.0464 | 0.0462 | 19.0 |
| No log | 3.96 | 312 | nan | 0.0521 | 0.0088 | 0.0464 | 0.0462 | 19.0 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3