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# BERT2BERT_finetuned

This model is a fine-tuned version of [JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0](https://huggingface.co/JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1672
- Bleu: 96.7679
- Em: 0.6307
- Rm: 0.7482
- Gen Len: 75.6355

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 300.0

### Training results

| Training Loss | Epoch  | Step  | Bleu    | Em     | Gen Len | Validation Loss | Rm     |
|:-------------:|:------:|:-----:|:-------:|:------:|:-------:|:---------------:|:------:|
| 3.4354        | 12.82  | 500   | 56.6427 | 0.0    | 70.5947 | 1.5065          | 0.0    |
| 0.8473        | 25.64  | 1000  | 90.5419 | 0.0192 | 76.9736 | 0.3859          | 0.0216 |
| 0.2049        | 38.46  | 1500  | 93.6495 | 0.0504 | 75.1655 | 0.2472          | 0.0671 |
| 0.1222        | 51.28  | 2000  | 93.8388 | 0.0959 | 75.6403 | 0.2338          | 0.1487 |
| 0.0923        | 64.1   | 2500  | 94.71   | 0.2158 | 75.8177 | 0.1944          | 0.2662 |
| 0.0752        | 76.92  | 3000  | 95.0458 | 0.2662 | 75.2638 | 0.1990          | 0.3022 |
| 0.0627        | 89.74  | 3500  | 95.3518 | 0.3429 | 76.9928 | 0.1957          | 0.3957 |
| 0.052         | 102.56 | 4000  | 95.5392 | 0.3837 | 76.1007 | 0.1861          | 0.4508 |
| 0.0457        | 115.38 | 4500  | 95.6692 | 0.4173 | 76.1727 | 0.1880          | 0.4892 |
| 0.0386        | 128.21 | 5000  | 95.9215 | 0.446  | 76.0168 | 0.1850          | 0.5276 |
| 0.0321        | 141.03 | 5500  | 95.931  | 0.4964 | 75.2566 | 0.1724          | 0.5875 |
| 0.026         | 153.85 | 6000  | 96.4317 | 0.5348 | 75.741  | 0.1687          | 0.6499 |
| 0.0242        | 166.67 | 6500  | 96.197  | 0.5372 | 76.1127 | 0.1707          | 0.6403 |
| 0.0193        | 179.49 | 7000  | 96.3422 | 0.5564 | 75.3933 | 0.1643          | 0.6691 |
| 0.0164        | 192.31 | 7500  | 96.5278 | 0.5779 | 75.4508 | 0.1650          | 0.693  |
| 0.0139        | 205.13 | 8000  | 96.6382 | 0.6091 | 75.9592 | 0.1668          | 0.7314 |
| 0.012         | 217.95 | 8500  | 96.5488 | 0.6163 | 76.0024 | 0.1644          | 0.729  |
| 0.0106        | 230.77 | 9000  | 96.6353 | 0.6091 | 75.5468 | 0.1653          | 0.7266 |
| 0.0093        | 243.59 | 9500  | 96.8984 | 0.6331 | 75.7242 | 0.1663          | 0.7482 |
| 0.0084        | 256.41 | 10000 | 96.6199 | 0.6331 | 75.3885 | 0.1676          | 0.7482 |
| 0.0076        | 269.23 | 10500 | 0.1678  | 96.5038| 0.6283  | 0.7482          | 75.3453|
| 0.007         | 282.05 | 11000 | 0.1669  | 96.7187| 0.6355  | 0.7458          | 75.9281|
| 0.0065        | 294.87 | 11500 | 0.1672  | 96.7679| 0.6307  | 0.7482          | 75.6355|


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "BERT2BERT_finetuned", "results": []}]}
transformers pytorch tensorboard encoder-decoder text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

BERT2BERT\_finetuned
====================


This model is a fine-tuned version of JulienRPA/BERT2BERT\_pretrained\_LC-QuAD\_2.0 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1672
* Bleu: 96.7679
* Em: 0.6307
* Rm: 0.7482
* Gen Len: 75.6355


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: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 300.0


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 300.0 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 300.0 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3