Text_Summarization_model_12042024
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5629
- Rouge1: 0.2385
- Rouge2: 0.19
- Rougel: 0.2296
- Rougelsum: 0.2296
- 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|---|
| 1.8769 | 1.0 | 4691 | 1.6645 | 0.2336 | 0.1826 | 0.2236 | 0.2236 | 19.0 |
| 1.826 | 2.0 | 9382 | 1.5972 | 0.2367 | 0.1869 | 0.2273 | 0.2273 | 19.0 |
| 1.7617 | 3.0 | 14073 | 1.5720 | 0.2384 | 0.1898 | 0.2294 | 0.2294 | 19.0 |
| 1.7664 | 4.0 | 18764 | 1.5629 | 0.2385 | 0.19 | 0.2296 | 0.2296 | 19.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
google-t5/t5-small