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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: 0.3690
- Bleu: 0.0229
- Rouge1: 0.4217
- Rouge2: 0.3443
- Avg Length: 17.1574

## 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  | 0.4444          | 0.0215 | 0.369  | 0.3113 | 18.0234    |
| 1.954         | 2.0   | 750  | 0.3842          | 0.0214 | 0.398  | 0.3329 | 16.9644    |
| 0.3621        | 3.0   | 1125 | 0.3631          | 0.0238 | 0.4089 | 0.3377 | 17.3726    |
| 0.3166        | 4.0   | 1500 | 0.3472          | 0.0214 | 0.4152 | 0.3413 | 16.956     |
| 0.3166        | 5.0   | 1875 | 0.3403          | 0.0238 | 0.4191 | 0.3437 | 17.198     |
| 0.2846        | 6.0   | 2250 | 0.3333          | 0.0247 | 0.414  | 0.3456 | 17.5016    |
| 0.2605        | 7.0   | 2625 | 0.3357          | 0.022  | 0.4215 | 0.346  | 17.023     |
| 0.2422        | 8.0   | 3000 | 0.3317          | 0.0287 | 0.4277 | 0.3522 | 17.658     |
| 0.2422        | 9.0   | 3375 | 0.3334          | 0.0252 | 0.4288 | 0.351  | 17.3284    |
| 0.2221        | 10.0  | 3750 | 0.3347          | 0.0225 | 0.4215 | 0.3435 | 17.1506    |
| 0.2073        | 11.0  | 4125 | 0.3392          | 0.0258 | 0.4234 | 0.3498 | 17.4554    |
| 0.194         | 12.0  | 4500 | 0.3445          | 0.0245 | 0.427  | 0.3488 | 17.2398    |
| 0.194         | 13.0  | 4875 | 0.3614          | 0.0253 | 0.4284 | 0.3489 | 17.3902    |
| 0.1789        | 14.0  | 5250 | 0.3556          | 0.0276 | 0.4261 | 0.3504 | 17.5164    |
| 0.1681        | 15.0  | 5625 | 0.3690          | 0.0229 | 0.4217 | 0.3443 | 17.1574    |


### 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: 0.3690
* Bleu: 0.0229
* Rouge1: 0.4217
* Rouge2: 0.3443
* Avg Length: 17.1574


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