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# t5-small-codesearchnet-multilang-python

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: 0.8169
- Bleu: 0.0012
- Rouge1: 0.1986
- Rouge2: 0.0594
- Avg Length: 14.004

## 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  | 0.9943          | 0.0003 | 0.1637 | 0.0365 | 13.785     |
| 2.445         | 2.0   | 750  | 0.8991          | 0.0002 | 0.171  | 0.041  | 13.0266    |
| 0.8324        | 3.0   | 1125 | 0.8509          | 0.001  | 0.1931 | 0.0499 | 14.9474    |
| 0.7567        | 4.0   | 1500 | 0.8184          | 0.0015 | 0.2019 | 0.0561 | 14.9598    |
| 0.7567        | 5.0   | 1875 | 0.8002          | 0.0016 | 0.2097 | 0.0608 | 14.496     |
| 0.6947        | 6.0   | 2250 | 0.7793          | 0.0016 | 0.2138 | 0.0631 | 14.6502    |
| 0.658         | 7.0   | 2625 | 0.7721          | 0.0018 | 0.2104 | 0.0617 | 15.2       |
| 0.6186        | 8.0   | 3000 | 0.7669          | 0.0023 | 0.2175 | 0.0642 | 15.7472    |
| 0.6186        | 9.0   | 3375 | 0.7792          | 0.0027 | 0.2218 | 0.0664 | 15.862     |
| 0.58          | 10.0  | 3750 | 0.7629          | 0.0005 | 0.1985 | 0.0591 | 12.0968    |
| 0.5533        | 11.0  | 4125 | 0.7826          | 0.0027 | 0.2126 | 0.0631 | 16.9146    |
| 0.5279        | 12.0  | 4500 | 0.7907          | 0.0025 | 0.2144 | 0.0626 | 16.656     |
| 0.5279        | 13.0  | 4875 | 0.7827          | 0.0007 | 0.2019 | 0.0606 | 12.4734    |
| 0.4964        | 14.0  | 5250 | 0.7933          | 0.0023 | 0.2204 | 0.0674 | 15.344     |
| 0.4803        | 15.0  | 5625 | 0.8169          | 0.0012 | 0.1986 | 0.0594 | 14.004     |


### 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", "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
=======================================


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


* Loss: 0.8169
* Bleu: 0.0012
* Rouge1: 0.1986
* Rouge2: 0.0594
* Avg Length: 14.004


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