Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use Patcas/v9.7-codet5-bert-finetuned-code_function-to-test_case_function with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Patcas/v9.7-codet5-bert-finetuned-code_function-to-test_case_function with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Patcas/v9.7-codet5-bert-finetuned-code_function-to-test_case_function") model = AutoModelForSeq2SeqLM.from_pretrained("Patcas/v9.7-codet5-bert-finetuned-code_function-to-test_case_function", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Patcas/v9.7-codet5-bert-finetuned-code_function-to-test_case_function: direct link, hf CLI and curl.
- Browser
- Download file 1.85 kB
-
https://huggingface.co/Patcas/v9.7-codet5-bert-finetuned-code_function-to-test_case_function/resolve/main/README.md
- Command line
-
hf download hf://Patcas/v9.7-codet5-bert-finetuned-code_function-to-test_case_function/README.md
-
curl -L -o README.md https://huggingface.co/Patcas/v9.7-codet5-bert-finetuned-code_function-to-test_case_function/resolve/main/README.md
1.85 kB
metadata
license: apache-2.0
base_model: Salesforce/codet5-base
tags:
- generated_from_trainer
model-index:
- name: v9.7-codet5-bert-finetuned-code_function-to-test_case_function
results: []
v9.7-codet5-bert-finetuned-code_function-to-test_case_function
This model is a fine-tuned version of Salesforce/codet5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3226
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 10 | 3.4893 |
| No log | 2.0 | 20 | 2.9930 |
| No log | 3.0 | 30 | 2.7990 |
| No log | 4.0 | 40 | 2.6546 |
| No log | 5.0 | 50 | 2.5664 |
| No log | 6.0 | 60 | 2.4976 |
| No log | 7.0 | 70 | 2.4303 |
| No log | 8.0 | 80 | 2.3481 |
| No log | 9.0 | 90 | 2.3255 |
| No log | 10.0 | 100 | 2.3226 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1