metadata
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: test_sum_abs_t5_small_wasa_stops
results: []
test_sum_abs_t5_small_wasa_stops
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8601
- Rouge1: 0.3823
- Rouge2: 0.2702
- Rougel: 0.3451
- Rougelsum: 0.3454
- Gen Len: 18.9864
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
- 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 |
---|---|---|---|---|---|---|---|---|
1.0591 | 1.0 | 1764 | 0.9275 | 0.3767 | 0.2652 | 0.3403 | 0.3404 | 18.9787 |
0.9758 | 2.0 | 3528 | 0.8813 | 0.3817 | 0.2702 | 0.3448 | 0.345 | 18.9819 |
0.9575 | 3.0 | 5292 | 0.8648 | 0.3818 | 0.2692 | 0.3445 | 0.3446 | 18.987 |
0.9435 | 4.0 | 7056 | 0.8601 | 0.3823 | 0.2702 | 0.3451 | 0.3454 | 18.9864 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2