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# my-text-to-sparql-id-combined-dataset-t5-base-2023-05-07_15-33

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3333
- Gen Len: 19.0
- Bertscorer-p: 0.5060
- Bertscorer-r: 0.1130
- Bertscorer-f1: 0.3017
- Sacrebleu-score: 6.1737
- Sacrebleu-precisions: [78.41306042322238, 65.32969938575438, 54.170628484068835, 48.69315639562166]
- Bleu-bp: 0.1018

## 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: 0.0003
- 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Gen Len | Bertscorer-p | Bertscorer-r | Bertscorer-f1 | Sacrebleu-score | Sacrebleu-precisions                                                          | Bleu-bp |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:------------:|:-------------:|:---------------:|:-----------------------------------------------------------------------------:|:-------:|
| 0.3541        | 1.0   | 7822 | 0.3333          | 19.0    | 0.5060       | 0.1130       | 0.3017        | 6.1737          | [78.41306042322238, 65.32969938575438, 54.170628484068835, 48.69315639562166] | 0.1018  |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "my-text-to-sparql-id-combined-dataset-t5-base-2023-05-07_15-33", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

my-text-to-sparql-id-combined-dataset-t5-base-2023-05-07\_15-33
===============================================================


This model is a fine-tuned version of t5-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3333
* Gen Len: 19.0
* Bertscorer-p: 0.5060
* Bertscorer-r: 0.1130
* Bertscorer-f1: 0.3017
* Sacrebleu-score: 6.1737
* Sacrebleu-precisions: [78.41306042322238, 65.32969938575438, 54.170628484068835, 48.69315639562166]
* Bleu-bp: 0.1018


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: 0.0003
* 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: 1


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* 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: 1 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* 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: 1 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3