File size: 1,611 Bytes
f2affe3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
---
license: apache-2.0
base_model: Falconsai/medical_summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-s19
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-s19
This model is a fine-tuned version of [Falconsai/medical_summarization](https://huggingface.co/Falconsai/medical_summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4137
- Rouge1: 33.1554
- Rouge2: 15.9465
- Rougel: 28.0028
- Rougelsum: 28.0647
- Gen Len: 17.3715
## 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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.8319 | 1.0 | 625 | 2.4137 | 33.1554 | 15.9465 | 28.0028 | 28.0647 | 17.3715 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|