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

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: 0.4172
- Bleu: 0.0344
- Rouge1: 0.3447
- Rouge2: 0.2223
- Avg Length: 17.0756

## 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  | 0.4953          | 0.0246 | 0.2585 | 0.1659 | 17.688     |
| 2.1147        | 2.0   | 750  | 0.4376          | 0.0263 | 0.293  | 0.1912 | 17.044     |
| 0.4761        | 3.0   | 1125 | 0.4125          | 0.0317 | 0.2964 | 0.1965 | 17.4636    |
| 0.4163        | 4.0   | 1500 | 0.3980          | 0.0277 | 0.3095 | 0.2015 | 16.3844    |
| 0.4163        | 5.0   | 1875 | 0.3868          | 0.0293 | 0.325  | 0.2082 | 16.6804    |
| 0.3808        | 6.0   | 2250 | 0.3815          | 0.0288 | 0.3232 | 0.2089 | 16.7996    |
| 0.352         | 7.0   | 2625 | 0.3720          | 0.024  | 0.3225 | 0.2119 | 15.8864    |
| 0.3295        | 8.0   | 3000 | 0.3695          | 0.0198 | 0.3142 | 0.2118 | 15.4172    |
| 0.3295        | 9.0   | 3375 | 0.3736          | 0.0305 | 0.343  | 0.2206 | 16.8566    |
| 0.3052        | 10.0  | 3750 | 0.3811          | 0.0316 | 0.3442 | 0.2215 | 16.8834    |
| 0.2887        | 11.0  | 4125 | 0.3775          | 0.023  | 0.3262 | 0.2149 | 15.6226    |
| 0.2799        | 12.0  | 4500 | 0.3793          | 0.034  | 0.3397 | 0.2186 | 16.6344    |
| 0.2799        | 13.0  | 4875 | 0.3875          | 0.0312 | 0.3389 | 0.2192 | 16.7964    |
| 0.2517        | 14.0  | 5250 | 0.3833          | 0.0337 | 0.3387 | 0.22   | 16.9076    |
| 0.2409        | 15.0  | 5625 | 0.4172          | 0.0344 | 0.3447 | 0.2223 | 17.0756    |


### 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-javascript-go", "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-javascript-go
==========================================================


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


* Loss: 0.4172
* Bleu: 0.0344
* Rouge1: 0.3447
* Rouge2: 0.2223
* Avg Length: 17.0756


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