
# Santacoder code-to-text

This model is a fine-tuned version of [bigcode/santacoder](https://huggingface.co/bigcode/santacoder) on
[copdeparrot/gitub-jupyter-code-to-text](https://huggingface.co/datasets/codeparrot/github-jupyter-code-to-text).


## Training procedure

The model was trained on 4 A100 for 3h with the following hyperparameters were used during training on 4 A100:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 800

{"license": "openrail", "library_name": "transformers", "tags": ["code"], "datasets": ["codeparrot/github-jupyter-code-to-text"]}
transformers pytorch gpt2 text-generation code custom_code dataset:codeparrot/github-jupyter-code-to-text license:openrail autotrain_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #code #custom_code #dataset-codeparrot/github-jupyter-code-to-text #license-openrail #autotrain_compatible #has_space #text-generation-inference #region-us 


# Santacoder code-to-text

This model is a fine-tuned version of bigcode/santacoder on
copdeparrot/gitub-jupyter-code-to-text.


## Training procedure

The model was trained on 4 A100 for 3h with the following hyperparameters were used during training on 4 A100:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 800

# Santacoder code-to-text

This model is a fine-tuned version of bigcode/santacoder on
copdeparrot/gitub-jupyter-code-to-text. ## Training procedure

The model was trained on 4 A100 for 3h with the following hyperparameters were used during training on 4 A100:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 800
TAGS
#transformers #pytorch #gpt2 #text-generation #code #custom_code #dataset-codeparrot/github-jupyter-code-to-text #license-openrail #autotrain_compatible #has_space #text-generation-inference #region-us 
 # Santacoder code-to-text

This model is a fine-tuned version of bigcode/santacoder on
copdeparrot/gitub-jupyter-code-to-text. ## Training procedure

The model was trained on 4 A100 for 3h with the following hyperparameters were used during training on 4 A100:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 800
TAGS
#transformers #pytorch #gpt2 #text-generation #code #custom_code #dataset-codeparrot/github-jupyter-code-to-text #license-openrail #autotrain_compatible #has_space #text-generation-inference #region-us 
# Santacoder code-to-text

This model is a fine-tuned version of bigcode/santacoder on
copdeparrot/gitub-jupyter-code-to-text.## Training procedure

The model was trained on 4 A100 for 3h with the following hyperparameters were used during training on 4 A100:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 800