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---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: tidy-tab-model
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. -->
# tidy-tab-model
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5060
- Rouge1: 0.3341
- Rouge2: 0.1528
- Rougel: 0.3104
- Rougelsum: 0.3125
- Gen Len: 17.75
## 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: 8
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 7 | 4.4385 | 0.1922 | 0.0928 | 0.1885 | 0.1862 | 17.9167 |
| No log | 2.0 | 14 | 4.1803 | 0.2265 | 0.1136 | 0.2229 | 0.2214 | 17.75 |
| No log | 3.0 | 21 | 3.9826 | 0.2505 | 0.0972 | 0.2495 | 0.2517 | 17.1667 |
| No log | 4.0 | 28 | 3.8140 | 0.3166 | 0.131 | 0.3117 | 0.3168 | 17.5 |
| No log | 5.0 | 35 | 3.6817 | 0.3442 | 0.1594 | 0.3194 | 0.3211 | 17.4167 |
| No log | 6.0 | 42 | 3.5924 | 0.3341 | 0.1528 | 0.3104 | 0.3125 | 17.75 |
| No log | 7.0 | 49 | 3.5356 | 0.3341 | 0.1528 | 0.3104 | 0.3125 | 17.75 |
| No log | 8.0 | 56 | 3.5060 | 0.3341 | 0.1528 | 0.3104 | 0.3125 | 17.75 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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