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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: T5_base_title
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_base_title
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0487
- Rouge1: 0.3848
- Rouge2: 0.1901
- Rougel: 0.3297
- Rougelsum: 0.3288
- Gen Len: 16.795
## 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 200 | 2.0966 | 0.3525 | 0.165 | 0.2921 | 0.2934 | 17.4 |
| No log | 2.0 | 400 | 2.0533 | 0.3706 | 0.1775 | 0.3145 | 0.3147 | 16.52 |
| 2.2032 | 3.0 | 600 | 2.0453 | 0.3754 | 0.1867 | 0.3226 | 0.3227 | 16.68 |
| 2.2032 | 4.0 | 800 | 2.0383 | 0.379 | 0.1887 | 0.3246 | 0.3243 | 16.36 |
| 1.8535 | 5.0 | 1000 | 2.0376 | 0.3849 | 0.1881 | 0.3269 | 0.3267 | 16.755 |
| 1.8535 | 6.0 | 1200 | 2.0416 | 0.378 | 0.1792 | 0.3236 | 0.3228 | 16.84 |
| 1.8535 | 7.0 | 1400 | 2.0445 | 0.3805 | 0.1848 | 0.3249 | 0.3248 | 16.65 |
| 1.692 | 8.0 | 1600 | 2.0484 | 0.3876 | 0.187 | 0.3289 | 0.3285 | 16.845 |
| 1.692 | 9.0 | 1800 | 2.0473 | 0.3891 | 0.1912 | 0.3325 | 0.332 | 16.815 |
| 1.6276 | 10.0 | 2000 | 2.0487 | 0.3848 | 0.1901 | 0.3297 | 0.3288 | 16.795 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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