transformers safetensors t5 text2text-generation generated_from_trainer dataset:code_search_net base_model:google-t5/t5-base base_model:finetune:google-t5/t5-base license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-base
datasets:
- code_search_net
license: apache-2.0
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: base_model_custom_tokenizer
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: code_search_net
      type: code_search_net
      config: python
      split: test
      args: python
    metrics:
    - type: bleu
      value: 0.0418696919911329
      name: Bleu
---

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# base_model_custom_tokenizer

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the code_search_net dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9297
- Bleu: 0.0419
- Precisions: [0.16646886171883812, 0.051341379400381214, 0.025538496667355304, 0.01408001744219341]
- Brevity Penalty: 1.0
- Length Ratio: 1.9160
- Translation Length: 1515803
- Reference Length: 791127

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step   | Bleu   | Brevity Penalty | Length Ratio | Validation Loss | Precisions                                                                              | Reference Length | Translation Length |
|:-------------:|:-----:|:------:|:------:|:---------------:|:------------:|:---------------:|:---------------------------------------------------------------------------------------:|:----------------:|:------------------:|
| 3.9604        | 1.0   | 25762  | 0.0311 | 1.0             | 2.0901       | 3.8577          | [0.12981129473835085, 0.037916946342151155, 0.018860549385742668, 0.010123458812721054] | 791127           | 1653531            |
| 3.7556        | 2.0   | 51524  | 0.0304 | 1.0             | 2.0887       | 3.5650          | [0.12978779415458075, 0.037579383019195466, 0.018120049525730805, 0.00967159578808246]  | 791127           | 1652405            |
| 3.5524        | 3.0   | 77286  | 0.0337 | 1.0             | 2.0745       | 3.4150          | [0.1400710094937268, 0.04118126290523918, 0.0203289377688518, 0.01095848654003696]      | 791127           | 1641189            |
| 3.4698        | 4.0   | 103048 | 0.0340 | 1.0             | 2.0788       | 3.3056          | [0.14277601173291565, 0.041700438046903744, 0.020391137906857287, 0.010998711103394348] | 791127           | 1644604            |
| 3.3163        | 5.0   | 128810 | 0.0377 | 1.0             | 2.0193       | 3.2312          | [0.15481298837386176, 0.04617083876865068, 0.022825576079888228, 0.012408874977873952]  | 791127           | 1597521            |
| 3.2458        | 6.0   | 154572 | 0.0382 | 1.0             | 1.9276       | 3.1719          | [0.1593547435203856, 0.04704355006890476, 0.023023369844916947, 0.012389103841794662]   | 791127           | 1524975            |
| 3.1574        | 7.0   | 180334 | 0.0373 | 1.0             | 2.0231       | 3.1267          | [0.15301209486452477, 0.04557636504175273, 0.022512350851579006, 0.012331176442211789]  | 791127           | 1600514            |
| 3.1398        | 8.0   | 206096 | 0.0386 | 1.0             | 1.9724       | 3.0893          | [0.1577822509066417, 0.04745355472604797, 0.023342833604973825, 0.012766267921605798]   | 791127           | 1560429            |
| 3.0691        | 9.0   | 231858 | 0.0399 | 1.0             | 1.9159       | 3.0574          | [0.16179891666501725, 0.0490436396529825, 0.024170720153435545, 0.013205125551162357]   | 791127           | 1515690            |
| 3.0536        | 10.0  | 257620 | 0.0410 | 1.0             | 1.8550       | 3.0321          | [0.1656489584760067, 0.05027218283158705, 0.024914277684092188, 0.013668271409759075]   | 791127           | 1467513            |
| 3.0379        | 11.0  | 283382 | 0.0404 | 1.0             | 1.8928       | 3.0082          | [0.1630008107267023, 0.049590989569352824, 0.02452930558336929, 0.013463575807213558]   | 791127           | 1497422            |
| 3.0183        | 12.0  | 309144 | 0.0409 | 1.0             | 1.9428       | 2.9924          | [0.16253787482001938, 0.049984123536708294, 0.02498794115282579, 0.01380309274144192]   | 791127           | 1536971            |
| 2.9442        | 13.0  | 334906 | 0.0413 | 1.0             | 1.9288       | 2.9773          | [0.16426924674922966, 0.05052962811986506, 0.025225357778251727, 0.013893123599262487]  | 791127           | 1525946            |
| 2.9746        | 14.0  | 360668 | 0.0411 | 1.0             | 1.9154       | 2.9622          | [0.16395222297528722, 0.050373776569881686, 0.02506334156586741, 0.013817874614866431]  | 791127           | 1515289            |
| 2.9556        | 15.0  | 386430 | 0.0416 | 1.0             | 1.8903       | 2.9505          | [0.16631916674913938, 0.05114349827528396, 0.025291167834370104, 0.013919582587470626]  | 791127           | 1495444            |
| 2.9423        | 16.0  | 412192 | 0.0415 | 1.0             | 1.9161       | 2.9441          | [0.1656048056193977, 0.050903942131636466, 0.02527336097239107, 0.013901882376966617]   | 791127           | 1515892            |
| 2.9257        | 17.0  | 437954 | 0.0417 | 1.0             | 1.9204       | 2.9387          | [0.16566872310834463, 0.051149695919205686, 0.02547749541013215, 0.01403388257902964]   | 791127           | 1519291            |
| 2.9023        | 18.0  | 463716 | 0.0417 | 1.0             | 1.9252       | 2.9331          | [0.16569868978430946, 0.05118214894137258, 0.025432645752525008, 0.014019028423183673]  | 791127           | 1523108            |
| 2.946         | 19.0  | 489478 | 0.0420 | 1.0             | 1.9138       | 2.9301          | [0.16682044755191178, 0.051534782710695386, 0.02563003483561942, 0.014141190855303378]  | 791127           | 1514059            |
| 2.8761        | 20.0  | 515240 | 2.9297 | 0.0419          | [0.16646886171883812, 0.051341379400381214, 0.025538496667355304, 0.01408001744219341]| 1.0             | 1.9160                                                                                  | 1515803          | 791127             |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
