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# flan-t5-small-codesearchnet-python

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0764
- Bleu: 0.0349
- Rouge1: 0.6244
- Rouge2: 0.6055
- Avg Length: 16.9912

## 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  | 0.0636          | 0.0364 | 0.6253 | 0.6076 | 17.029     |
| 5.5166        | 2.0   | 750  | 0.0553          | 0.0351 | 0.6259 | 0.6081 | 16.9996    |
| 0.0485        | 3.0   | 1125 | 0.0537          | 0.0351 | 0.6258 | 0.6083 | 16.99      |
| 0.0409        | 4.0   | 1500 | 0.0524          | 0.0351 | 0.6258 | 0.6082 | 16.9942    |
| 0.0409        | 5.0   | 1875 | 0.0524          | 0.0351 | 0.6261 | 0.6086 | 16.997     |
| 0.0345        | 6.0   | 2250 | 0.0526          | 0.0351 | 0.6258 | 0.6081 | 16.9936    |
| 0.0303        | 7.0   | 2625 | 0.0533          | 0.035  | 0.6254 | 0.6076 | 16.991     |
| 0.0256        | 8.0   | 3000 | 0.0566          | 0.035  | 0.6257 | 0.6074 | 16.9964    |
| 0.0256        | 9.0   | 3375 | 0.0592          | 0.0349 | 0.6253 | 0.6074 | 16.998     |
| 0.0205        | 10.0  | 3750 | 0.0612          | 0.0351 | 0.6255 | 0.6073 | 16.9932    |
| 0.0185        | 11.0  | 4125 | 0.0639          | 0.035  | 0.6257 | 0.6079 | 16.996     |
| 0.0157        | 12.0  | 4500 | 0.0698          | 0.035  | 0.625  | 0.6064 | 16.9944    |
| 0.0157        | 13.0  | 4875 | 0.0720          | 0.035  | 0.6246 | 0.6062 | 16.991     |
| 0.0131        | 14.0  | 5250 | 0.0745          | 0.035  | 0.6247 | 0.6062 | 16.9986    |
| 0.0128        | 15.0  | 5625 | 0.0764          | 0.0349 | 0.6244 | 0.6055 | 16.9912    |


### 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": "flan-t5-small-codesearchnet-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 

flan-t5-small-codesearchnet-python
==================================


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


* Loss: 0.0764
* Bleu: 0.0349
* Rouge1: 0.6244
* Rouge2: 0.6055
* Avg Length: 16.9912


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