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---
license: other
tags:
- generated_from_trainer
- google/gemma
- PyTorch
- transformers
- trl
- peft
- tensorboard
model-index:
- name: pygemma-2b-ultra
  results: []
datasets:
- Vezora/Tested-143k-Python-Alpaca
language:
- en
license_name: gemma-terms-of-use
license_link: https://ai.google.dev/gemma/terms
base_model: google/gemma-2b
widget:
  - example_title: Compute Sum
    messages:
      - role: system
        content: >
          Welcome to PyGemma, your AI-powered Python assistant. I'm here to help you answer common questions about the Python programming language. Let's dive into Python!
          
          Please note:
          - I strive to provide accurate and reliable information, but I'm not perfect. If you notice any inaccuracies, please let me know.
          - I'm committed to maintaining a safe and respectful environment. Please avoid using toxic or harmful language.
          - I'm continuously learning and improving. If you notice any inconsistencies in my responses, I appreciate your patience and feedback.
      - role: user
        content: Create a function to calculate the sum of a sequence of integers.
inference:
  parameters:
    temperature: 0.1
    max_new_tokens: 1024
    top_p: 0.95
    top_k: 50

pipeline_tag: text-generation
---

# Model Card for pygemma-2b-ultra:

🐍💬🤖


**pygemma-2b-ultra** is a language model that is trained to act as Python assistant. It is a finetuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) that was trained using `SFTTrainer` on publicly available dataset
[Vezora/Tested-143k-Python-Alpaca](https://huggingface.co/datasets/Vezora/Tested-143k-Python-Alpaca).


## Training Metrics

[The training metrics can be found on **TensorBoard**](https://huggingface.co/Menouar/pygemma-2b-ultra/tensorboard).


## Training hyperparameters

The following hyperparameters were used during the training:


- output_dir: peft-lora-model
 
- overwrite_output_dir: True
 
- do_train: False
 
- do_eval: False
 
- do_predict: False
 
- evaluation_strategy: no
 
- prediction_loss_only: False
 
- per_device_train_batch_size: 2
 
- per_device_eval_batch_size: None
 
- per_gpu_train_batch_size: None
 
- per_gpu_eval_batch_size: None
 
- gradient_accumulation_steps: 4
 
- eval_accumulation_steps: None
 
- eval_delay: 0
 
- learning_rate: 2e-05
 
- weight_decay: 0.0
 
- adam_beta1: 0.9
 
- adam_beta2: 0.999
 
- adam_epsilon: 1e-08
 
- max_grad_norm: 0.3
 
- num_train_epochs: 1
 
- max_steps: -1
 
- lr_scheduler_type: cosine
 
- lr_scheduler_kwargs: {}
 
- warmup_ratio: 0.1
 
- warmup_steps: 0
 
- log_level: passive
 
- log_level_replica: warning
 
- log_on_each_node: True
 
- logging_dir: peft-lora-model/runs/Mar22_07-15-06_2013f91d074a
 
- logging_strategy: steps
 
- logging_first_step: False
 
- logging_steps: 10
 
- logging_nan_inf_filter: True
 
- save_strategy: epoch
 
- save_steps: 500
 
- save_total_limit: None
 
- save_safetensors: True
 
- save_on_each_node: False
 
- save_only_model: False
 
- no_cuda: False
 
- use_cpu: False
 
- use_mps_device: False
 
- seed: 42
 
- data_seed: None
 
- jit_mode_eval: False
 
- use_ipex: False
 
- bf16: True
 
- fp16: False
 
- fp16_opt_level: O1
 
- half_precision_backend: auto
 
- bf16_full_eval: False
 
- fp16_full_eval: False
 
- tf32: None
 
- local_rank: 0
 
- ddp_backend: None
 
- tpu_num_cores: None
 
- tpu_metrics_debug: False
 
- debug: []
 
- dataloader_drop_last: False
 
- eval_steps: None
 
- dataloader_num_workers: 0
 
- dataloader_prefetch_factor: None
 
- past_index: -1
 
- run_name: peft-lora-model
 
- disable_tqdm: False
 
- remove_unused_columns: True
 
- label_names: None
 
- load_best_model_at_end: False
 
- metric_for_best_model: None
 
- greater_is_better: None
 
- ignore_data_skip: False
 
- fsdp: []
 
- fsdp_min_num_params: 0
 
- fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
 
- fsdp_transformer_layer_cls_to_wrap: None
 
- accelerator_config: AcceleratorConfig(split_batches=False, dispatch_batches=None, even_batches=True, use_seedable_sampler=True)
 
- deepspeed: None
 
- label_smoothing_factor: 0.0
 
- optim: adamw_torch_fused
 
- optim_args: None
 
- adafactor: False
 
- group_by_length: False
 
- length_column_name: length
 
- report_to: ['tensorboard']
 
- ddp_find_unused_parameters: None
 
- ddp_bucket_cap_mb: None
 
- ddp_broadcast_buffers: None
 
- dataloader_pin_memory: True
 
- dataloader_persistent_workers: False
 
- skip_memory_metrics: True
 
- use_legacy_prediction_loop: False
 
- push_to_hub: False
 
- resume_from_checkpoint: None
 
- hub_model_id: None
 
- hub_strategy: every_save
 
- hub_token: None
 
- hub_private_repo: False
 
- hub_always_push: False
 
- gradient_checkpointing: True
 
- gradient_checkpointing_kwargs: {'use_reentrant': False}
 
- include_inputs_for_metrics: False
 
- fp16_backend: auto
 
- push_to_hub_model_id: None
 
- push_to_hub_organization: None
 
- push_to_hub_token: None
 
- mp_parameters: 
 
- auto_find_batch_size: False
 
- full_determinism: False
 
- torchdynamo: None
 
- ray_scope: last
 
- ddp_timeout: 1800
 
- torch_compile: False
 
- torch_compile_backend: None
 
- torch_compile_mode: None
 
- dispatch_batches: None
 
- split_batches: None
 
- include_tokens_per_second: False
 
- include_num_input_tokens_seen: False
 
- neftune_noise_alpha: None
 
- distributed_state: Distributed environment: NO
Num processes: 1
Process index: 0
Local process index: 0
Device: cuda

 
- _n_gpu: 1
 
- __cached__setup_devices: cuda:0
 
- deepspeed_plugin: None