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# t5-small-codesearchnet-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: 0.0785
- Bleu: 0.035
- Rouge1: 0.6257
- Rouge2: 0.6078
- Avg Length: 16.9954

## 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  | 0.0801          | 0.0358 | 0.6174 | 0.6    | 17.1074    |
| 1.6066        | 2.0   | 750  | 0.0674          | 0.036  | 0.6249 | 0.6068 | 17.0262    |
| 0.0584        | 3.0   | 1125 | 0.0632          | 0.0351 | 0.6255 | 0.6075 | 16.9962    |
| 0.0484        | 4.0   | 1500 | 0.0605          | 0.0351 | 0.6251 | 0.6071 | 17.003     |
| 0.0484        | 5.0   | 1875 | 0.0596          | 0.035  | 0.6255 | 0.6075 | 17.0012    |
| 0.0418        | 6.0   | 2250 | 0.0602          | 0.035  | 0.6258 | 0.608  | 16.9958    |
| 0.0377        | 7.0   | 2625 | 0.0593          | 0.0351 | 0.6259 | 0.6079 | 17.0004    |
| 0.033         | 8.0   | 3000 | 0.0618          | 0.035  | 0.6257 | 0.6078 | 17.0032    |
| 0.033         | 9.0   | 3375 | 0.0637          | 0.035  | 0.6257 | 0.6078 | 16.998     |
| 0.028         | 10.0  | 3750 | 0.0645          | 0.035  | 0.6257 | 0.6079 | 16.9984    |
| 0.0255        | 11.0  | 4125 | 0.0650          | 0.035  | 0.6255 | 0.6078 | 17.0008    |
| 0.0226        | 12.0  | 4500 | 0.0748          | 0.035  | 0.6254 | 0.6076 | 16.9976    |
| 0.0226        | 13.0  | 4875 | 0.0714          | 0.035  | 0.6256 | 0.6079 | 16.9954    |
| 0.019         | 14.0  | 5250 | 0.0747          | 0.0349 | 0.6253 | 0.6077 | 16.994     |
| 0.0172        | 15.0  | 5625 | 0.0785          | 0.035  | 0.6257 | 0.6078 | 16.9954    |


### 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-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-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: 0.0785
* Bleu: 0.035
* Rouge1: 0.6257
* Rouge2: 0.6078
* Avg Length: 16.9954


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