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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: 0.5955
- Bleu: 0.009
- Rouge1: 0.2321
- Rouge2: 0.0831
- Avg Length: 16.6192

## 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  | 0.7349          | 0.0028 | 0.1562 | 0.0364 | 16.436     |
| 2.3117        | 2.0   | 750  | 0.6613          | 0.0066 | 0.1818 | 0.0531 | 16.824     |
| 0.6755        | 3.0   | 1125 | 0.6233          | 0.007  | 0.1957 | 0.0594 | 16.931     |
| 0.5998        | 4.0   | 1500 | 0.6023          | 0.0082 | 0.202  | 0.063  | 16.7154    |
| 0.5998        | 5.0   | 1875 | 0.5925          | 0.0096 | 0.2154 | 0.0703 | 16.5468    |
| 0.5511        | 6.0   | 2250 | 0.5728          | 0.0091 | 0.2213 | 0.0774 | 15.7216    |
| 0.5147        | 7.0   | 2625 | 0.5670          | 0.0111 | 0.2311 | 0.0815 | 16.6658    |
| 0.4861        | 8.0   | 3000 | 0.5628          | 0.0089 | 0.2217 | 0.077  | 17.038     |
| 0.4861        | 9.0   | 3375 | 0.5598          | 0.0103 | 0.2311 | 0.0825 | 16.362     |
| 0.4526        | 10.0  | 3750 | 0.5589          | 0.0083 | 0.232  | 0.086  | 15.4298    |
| 0.4329        | 11.0  | 4125 | 0.5649          | 0.0098 | 0.2349 | 0.0839 | 16.5468    |
| 0.4102        | 12.0  | 4500 | 0.5633          | 0.0098 | 0.2366 | 0.0867 | 16.4136    |
| 0.4102        | 13.0  | 4875 | 0.5841          | 0.01   | 0.2385 | 0.0869 | 15.9864    |
| 0.3841        | 14.0  | 5250 | 0.5777          | 0.0128 | 0.2437 | 0.0894 | 16.842     |
| 0.3673        | 15.0  | 5625 | 0.5955          | 0.009  | 0.2321 | 0.0831 | 16.6192    |


### 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: 0.5955
* Bleu: 0.009
* Rouge1: 0.2321
* Rouge2: 0.0831
* Avg Length: 16.6192


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