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# t5-small-codesearchnet-multilang-python-java

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: 0.7015
- Bleu: 0.0045
- Rouge1: 0.2194
- Rouge2: 0.0741
- Avg Length: 15.9976

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Rouge1 | Rouge2 | Avg Length |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:----------:|
| No log        | 1.0   | 375  | 0.9005          | 0.0013 | 0.1397 | 0.0334 | 16.3976    |
| 2.3568        | 2.0   | 750  | 0.8036          | 0.0023 | 0.1737 | 0.0526 | 15.8896    |
| 0.7576        | 3.0   | 1125 | 0.7584          | 0.0021 | 0.1856 | 0.0558 | 15.3102    |
| 0.6778        | 4.0   | 1500 | 0.7298          | 0.0024 | 0.1922 | 0.0597 | 15.3544    |
| 0.6778        | 5.0   | 1875 | 0.7114          | 0.0037 | 0.2114 | 0.0704 | 15.7588    |
| 0.6206        | 6.0   | 2250 | 0.6949          | 0.0039 | 0.2093 | 0.0729 | 15.8088    |
| 0.5856        | 7.0   | 2625 | 0.6927          | 0.0042 | 0.2143 | 0.0711 | 16.5838    |
| 0.5447        | 8.0   | 3000 | 0.6867          | 0.005  | 0.2151 | 0.0717 | 17.2174    |
| 0.5447        | 9.0   | 3375 | 0.6895          | 0.0043 | 0.2179 | 0.0736 | 16.1068    |
| 0.5117        | 10.0  | 3750 | 0.6876          | 0.0038 | 0.2229 | 0.0777 | 15.5094    |
| 0.4892        | 11.0  | 4125 | 0.6800          | 0.0047 | 0.2201 | 0.0783 | 16.6902    |
| 0.4629        | 12.0  | 4500 | 0.6903          | 0.0047 | 0.2203 | 0.0771 | 16.7658    |
| 0.4629        | 13.0  | 4875 | 0.6947          | 0.0056 | 0.227  | 0.0777 | 16.8108    |
| 0.4355        | 14.0  | 5250 | 0.6999          | 0.0027 | 0.2028 | 0.0715 | 15.6776    |
| 0.418         | 15.0  | 5625 | 0.7015          | 0.0045 | 0.2194 | 0.0741 | 15.9976    |


### 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"], "metrics": ["bleu", "rouge"], "model-index": [{"name": "t5-small-codesearchnet-multilang-python-java", "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 

t5-small-codesearchnet-multilang-python-java
============================================


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


* Loss: 0.7015
* Bleu: 0.0045
* Rouge1: 0.2194
* Rouge2: 0.0741
* Avg Length: 15.9976


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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 10
* total\_train\_batch\_size: 80
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### 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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 10
* total\_train\_batch\_size: 80
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### 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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 10
* total\_train\_batch\_size: 80
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


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