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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-Clakmann-thesis-epoch10
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-Clakmann-thesis-epoch10
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: 1.5727
- Rouge1: 0.2268
- Rouge2: 0.0853
- Rougel: 0.215
- Rougelsum: 0.2157
- Gen Len: 14.2621
## 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.8844 | 1.0 | 5029 | 1.6766 | 0.2148 | 0.0756 | 0.2044 | 0.2045 | 13.7397 |
| 1.7073 | 2.0 | 10058 | 1.6168 | 0.2196 | 0.0792 | 0.2099 | 0.2102 | 13.8238 |
| 1.6487 | 3.0 | 15087 | 1.5948 | 0.2199 | 0.0794 | 0.209 | 0.2091 | 14.3399 |
| 1.5773 | 4.0 | 20116 | 1.5800 | 0.2252 | 0.0816 | 0.2157 | 0.2164 | 13.9383 |
| 1.5114 | 5.0 | 25145 | 1.5770 | 0.2229 | 0.0798 | 0.212 | 0.2126 | 14.2567 |
| 1.4688 | 6.0 | 30174 | 1.5703 | 0.2255 | 0.0848 | 0.2158 | 0.2164 | 13.9973 |
| 1.4283 | 7.0 | 35203 | 1.5673 | 0.2237 | 0.0834 | 0.2125 | 0.2129 | 14.0966 |
| 1.4166 | 8.0 | 40232 | 1.5702 | 0.2276 | 0.0866 | 0.2153 | 0.2159 | 14.3453 |
| 1.3978 | 9.0 | 45261 | 1.5706 | 0.2274 | 0.0864 | 0.216 | 0.2166 | 14.2272 |
| 1.3688 | 10.0 | 50290 | 1.5727 | 0.2268 | 0.0853 | 0.215 | 0.2157 | 14.2621 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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