---
license: apache-2.0
tags:
- simplification
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-base-clara-med
  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. -->

# flan-t5-base-clara-med

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2699
- Rouge1: 30.1376
- Rouge2: 16.8424
- Rougel: 27.9649
- Rougelsum: 27.9946

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 1.0   | 380   | 1.4710          | 27.6278 | 15.5057 | 25.9917 | 26.0601   |
| No log        | 2.0   | 760   | 1.3863          | 28.4324 | 15.8032 | 26.8023 | 26.8387   |
| 1.6476        | 3.0   | 1140  | 1.3494          | 28.6807 | 16.0854 | 26.9253 | 26.9743   |
| 1.6476        | 4.0   | 1520  | 1.3170          | 28.3434 | 15.6852 | 26.58   | 26.5937   |
| 1.3695        | 5.0   | 1900  | 1.3009          | 28.8006 | 15.819  | 26.8122 | 26.8756   |
| 1.3695        | 6.0   | 2280  | 1.2797          | 29.0521 | 16.4032 | 27.1802 | 27.1988   |
| 1.3695        | 7.0   | 2660  | 1.2744          | 29.2339 | 16.4583 | 27.3799 | 27.4091   |
| 1.2162        | 8.0   | 3040  | 1.2557          | 28.8177 | 16.2513 | 26.9967 | 27.028    |
| 1.2162        | 9.0   | 3420  | 1.2553          | 29.0411 | 16.4606 | 27.2912 | 27.3004   |
| 1.1232        | 10.0  | 3800  | 1.2540          | 29.0367 | 16.3896 | 27.2911 | 27.324    |
| 1.1232        | 11.0  | 4180  | 1.2500          | 29.3928 | 16.6718 | 27.4638 | 27.4877   |
| 1.1232        | 12.0  | 4560  | 1.2487          | 29.6046 | 16.7906 | 27.6814 | 27.6977   |
| 1.0389        | 13.0  | 4940  | 1.2542          | 29.4922 | 16.5255 | 27.5363 | 27.5904   |
| 1.0389        | 14.0  | 5320  | 1.2384          | 29.6472 | 16.707  | 27.6808 | 27.6988   |
| 0.9794        | 15.0  | 5700  | 1.2476          | 29.3771 | 16.2381 | 27.3751 | 27.3876   |
| 0.9794        | 16.0  | 6080  | 1.2437          | 29.4158 | 16.4003 | 27.3116 | 27.3409   |
| 0.9794        | 17.0  | 6460  | 1.2466          | 29.2787 | 16.4136 | 27.3256 | 27.3622   |
| 0.9276        | 18.0  | 6840  | 1.2530          | 29.4183 | 16.4244 | 27.325  | 27.3583   |
| 0.9276        | 19.0  | 7220  | 1.2582          | 29.743  | 16.7631 | 27.6997 | 27.7752   |
| 0.8851        | 20.0  | 7600  | 1.2560          | 29.5645 | 16.5834 | 27.5395 | 27.5622   |
| 0.8851        | 21.0  | 7980  | 1.2544          | 29.4893 | 16.4478 | 27.3961 | 27.4465   |
| 0.8851        | 22.0  | 8360  | 1.2593          | 29.785  | 16.6023 | 27.6214 | 27.6394   |
| 0.8578        | 23.0  | 8740  | 1.2588          | 30.008  | 16.8796 | 27.882  | 27.8989   |
| 0.8578        | 24.0  | 9120  | 1.2672          | 30.0112 | 16.6782 | 27.8556 | 27.8934   |
| 0.8347        | 25.0  | 9500  | 1.2668          | 29.6945 | 16.431  | 27.4398 | 27.4956   |
| 0.8347        | 26.0  | 9880  | 1.2642          | 29.9327 | 16.6105 | 27.798  | 27.8497   |
| 0.8347        | 27.0  | 10260 | 1.2674          | 30.0747 | 16.7768 | 27.9137 | 27.9609   |
| 0.8156        | 28.0  | 10640 | 1.2712          | 29.9504 | 16.6466 | 27.8371 | 27.8742   |
| 0.8156        | 29.0  | 11020 | 1.2692          | 30.2209 | 16.9038 | 28.0454 | 28.0982   |
| 0.8055        | 30.0  | 11400 | 1.2699          | 30.1376 | 16.8424 | 27.9649 | 27.9946   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0
- Datasets 2.8.0
- Tokenizers 0.12.1