Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use chathuranga-jayanath/codet5-small-v15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chathuranga-jayanath/codet5-small-v15 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("chathuranga-jayanath/codet5-small-v15") model = AutoModelForSeq2SeqLM.from_pretrained("chathuranga-jayanath/codet5-small-v15", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from chathuranga-jayanath/codet5-small-v15: direct link, hf CLI and curl.
- Browser
- Download file 1.62 kB
-
https://huggingface.co/chathuranga-jayanath/codet5-small-v15/resolve/main/README.md
- Command line
-
hf download hf://chathuranga-jayanath/codet5-small-v15/README.md
-
curl -L -o README.md https://huggingface.co/chathuranga-jayanath/codet5-small-v15/resolve/main/README.md
1.62 kB
metadata
license: apache-2.0
base_model: Salesforce/codet5-small
tags:
- generated_from_trainer
model-index:
- name: codet5-small-v15
results: []
codet5-small-v15
This model is a fine-tuned version of Salesforce/codet5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3626
- Bleu Score: 0.0067
- Gen Len: 14.3218
Model description
- prompt: [BUG]... [CONTEXT]... [METHOD]...
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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 171 | 0.4371 | 0.0067 | 14.237 |
| No log | 2.0 | 342 | 0.3753 | 0.0068 | 14.1711 |
| 0.5714 | 3.0 | 513 | 0.3626 | 0.0067 | 14.3218 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1