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---
tags:
- generated_from_trainer
- google/gemma
- PyTorch
- transformers
- trl
- peft
- tensorboard
model-index:
- name: pygemma
results: []
datasets:
- iamtarun/python_code_instructions_18k_alpaca
license_name: gemma-terms-of-use
license_link: https://ai.google.dev/gemma/terms
language:
- en
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!
- role: user
content: Create a function to calculate the sum of a sequence of integers.
pipeline_tag: text-generation
license: other
---
# Model Card for pygemma:
**pygemma** 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
[iamtarun/python_code_instructions_18k_alpaca](https://huggingface.co/datasets/iamtarun/python_code_instructions_18k_alpaca).
## Training hyperparameters
The following hyperparameters were used during the training:
- output_dir: peft-lora-pygemma
- 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: 3
- 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-pygemma/runs/Mar13_16-30-02_e65672b6422a
- 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-pygemma
- 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