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# 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

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "t5-small-medical_transcription", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation summarization generated_from_trainer doi:10.57967/hf/1246 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #summarization #generated_from_trainer #doi-10.57967/hf/1246 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-medical\_transcription
===============================


This model is a fine-tuned version of 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



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2


* base\_model:t5-small



### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2


* base\_model:t5-small
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #summarization #generated_from_trainer #doi-10.57967/hf/1246 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2


* base\_model:t5-small
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #summarization #generated_from_trainer #doi-10.57967/hf/1246 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### 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### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2


* base\_model:t5-small