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---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
model-index:
- name: t5_summarize
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5_summarize
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6492
- Evaluation Runtime: 28.4792
- Rounded Rouge Scores: {'rouge1': 0.174, 'rouge2': 0.0607, 'rougeL': 0.1367, 'rougeLsum': 0.1369}
## 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Evaluation Runtime | Rounded Rouge Scores |
|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------------------------------------------------------------------:|
| 2.7245 | 1.0 | 500 | 2.6814 | 29.2864 | {'rouge1': 0.1697, 'rouge2': 0.0584, 'rougeL': 0.1344, 'rougeLsum': 0.1345} |
| 2.7318 | 2.0 | 1000 | 2.6707 | 27.6464 | {'rouge1': 0.1735, 'rouge2': 0.0597, 'rougeL': 0.1372, 'rougeLsum': 0.1373} |
| 2.7164 | 3.0 | 1500 | 2.6646 | 27.3926 | {'rouge1': 0.1734, 'rouge2': 0.06, 'rougeL': 0.1371, 'rougeLsum': 0.1372} |
| 2.7054 | 4.0 | 2000 | 2.6600 | 27.3819 | {'rouge1': 0.1739, 'rouge2': 0.0599, 'rougeL': 0.1367, 'rougeLsum': 0.1368} |
| 2.6955 | 5.0 | 2500 | 2.6581 | 27.9933 | {'rouge1': 0.1731, 'rouge2': 0.0601, 'rougeL': 0.1361, 'rougeLsum': 0.1361} |
| 2.6865 | 6.0 | 3000 | 2.6535 | 28.2157 | {'rouge1': 0.1733, 'rouge2': 0.0603, 'rougeL': 0.1363, 'rougeLsum': 0.1364} |
| 2.6821 | 7.0 | 3500 | 2.6521 | 29.0758 | {'rouge1': 0.174, 'rouge2': 0.0606, 'rougeL': 0.1366, 'rougeLsum': 0.1369} |
| 2.681 | 8.0 | 4000 | 2.6508 | 31.2621 | {'rouge1': 0.1743, 'rouge2': 0.0609, 'rougeL': 0.1367, 'rougeLsum': 0.1369} |
| 2.6771 | 9.0 | 4500 | 2.6499 | 30.4251 | {'rouge1': 0.1735, 'rouge2': 0.0605, 'rougeL': 0.1364, 'rougeLsum': 0.1365} |
| 2.6751 | 10.0 | 5000 | 2.6492 | 28.4792 | {'rouge1': 0.174, 'rouge2': 0.0607, 'rougeL': 0.1367, 'rougeLsum': 0.1369} |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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