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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-medical_transcription
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-small-medical_transcription
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2564
- Rouge1: 0.4958
- Rouge2: 0.419
- Rougel: 0.4803
- Rougelsum: 0.481
- Gen Len: 18.1147
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.8608 | 1.0 | 559 | 0.3784 | 0.4243 | 0.3455 | 0.4076 | 0.4084 | 17.7384 |
| 0.4157 | 2.0 | 1118 | 0.3419 | 0.4245 | 0.3503 | 0.4092 | 0.4101 | 17.8612 |
| 0.3736 | 3.0 | 1677 | 0.3110 | 0.4436 | 0.3699 | 0.4274 | 0.4282 | 18.1187 |
| 0.3491 | 4.0 | 2236 | 0.3016 | 0.4613 | 0.3882 | 0.4452 | 0.4465 | 18.163 |
| 0.3253 | 5.0 | 2795 | 0.2844 | 0.4702 | 0.3962 | 0.4542 | 0.4545 | 18.1187 |
| 0.3094 | 6.0 | 3354 | 0.2735 | 0.4767 | 0.403 | 0.4607 | 0.4612 | 18.1308 |
| 0.2983 | 7.0 | 3913 | 0.2652 | 0.4853 | 0.4099 | 0.4692 | 0.4699 | 18.0201 |
| 0.2908 | 8.0 | 4472 | 0.2601 | 0.494 | 0.4175 | 0.4775 | 0.4783 | 18.1247 |
| 0.2808 | 9.0 | 5031 | 0.2571 | 0.4954 | 0.4169 | 0.4799 | 0.4811 | 18.0926 |
| 0.2803 | 10.0 | 5590 | 0.2564 | 0.4958 | 0.419 | 0.4803 | 0.481 | 18.1147 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
+ base_model:t5-small
|