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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: 0.7802
- Bleu: 0.0027
- Rouge1: 0.2097
- Rouge2: 0.0628
- Avg Length: 15.7496

## 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  | 0.9665          | 0.0004 | 0.1696 | 0.0384 | 14.1472    |
| 2.0677        | 2.0   | 750  | 0.8740          | 0.0004 | 0.1758 | 0.0428 | 13.38      |
| 0.8314        | 3.0   | 1125 | 0.8281          | 0.001  | 0.1925 | 0.0505 | 14.8026    |
| 0.7563        | 4.0   | 1500 | 0.7996          | 0.0017 | 0.2033 | 0.0582 | 14.9606    |
| 0.7563        | 5.0   | 1875 | 0.7780          | 0.0022 | 0.2117 | 0.0607 | 14.9434    |
| 0.6959        | 6.0   | 2250 | 0.7587          | 0.002  | 0.2135 | 0.0621 | 14.6926    |
| 0.6591        | 7.0   | 2625 | 0.7545          | 0.002  | 0.2073 | 0.0605 | 15.2818    |
| 0.6205        | 8.0   | 3000 | 0.7472          | 0.0024 | 0.2187 | 0.0674 | 15.051     |
| 0.6205        | 9.0   | 3375 | 0.7506          | 0.0031 | 0.2266 | 0.0696 | 15.6286    |
| 0.5822        | 10.0  | 3750 | 0.7449          | 0.001  | 0.206  | 0.063  | 13.1462    |
| 0.5553        | 11.0  | 4125 | 0.7573          | 0.0027 | 0.2148 | 0.0647 | 16.4076    |
| 0.5295        | 12.0  | 4500 | 0.7677          | 0.0026 | 0.2185 | 0.0658 | 15.8986    |
| 0.5295        | 13.0  | 4875 | 0.7595          | 0.0009 | 0.2052 | 0.0618 | 12.3528    |
| 0.4977        | 14.0  | 5250 | 0.7766          | 0.0035 | 0.2177 | 0.0636 | 16.6706    |
| 0.4818        | 15.0  | 5625 | 0.7802          | 0.0027 | 0.2097 | 0.0628 | 15.7496    |


### 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: 0.7802
* Bleu: 0.0027
* Rouge1: 0.2097
* Rouge2: 0.0628
* Avg Length: 15.7496


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