You can deploy this model and start earning money today!

CheapsetZero/
39bc2fec-c9d4-4af9-9ced-88a0914c04a4

Name: 39bc2fec-c9d4-4af9-9ced-88a0914c04a4
Availability: InStock

generated_from_trainer

unsloth/codegemma-7b

adapter

apache-2.0

Views

No views yet

See axolotl config

axolotl version: 0.4.1

yaml

adam_epsilon: 1e-6
adapter: lora
base_model: unsloth/codegemma-7b
bf16: true
chat_template: llama3
dataloader_num_workers: 0
dataloader_pin_memory: false
dataset_prepared_path: null
datasets:
- data_files:
  - bf5ab9b995188c06_train_data.json
  ds_type: json
  field: prompt
  path: /workspace/input_data/
  split: train
  type: completion
debug: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 2
flash_attention: false
fp16: false
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: CheapsetZero/39bc2fec-c9d4-4af9-9ced-88a0914c04a4
hub_strategy: checkpoint
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 64
lora_dropout: 0.05
lora_r: 32
lora_target_linear: true
lr_scheduler: constant_with_warmup
max_grad_norm: 1.0
max_steps: 4000
micro_batch_size: 16
mlflow_experiment_name: /tmp/bf5ab9b995188c06_train_data.json
model_type: AutoModelForCausalLM
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
sample_packing: false
save_safetensors: true
save_total_limit: 3
saves_per_epoch: 2
sequence_len: 512
strict: false
tf32: true
tokenizer_type: AutoTokenizer
torch_compile: false
train_on_inputs: false
trl:
  advantage_clip: 10.0
  beta: 0.1
  clip_rewards: true
  kl_penalty: kl
  max_completion_length: 256
  normalize_rewards: true
  num_generations: 8
  reward_clip_value: 10.0
  reward_funcs:
  - rewards_ea3eddcc-601a-41d2-8206-6d10300efc8b.reward_long_completions
  - rewards_ea3eddcc-601a-41d2-8206-6d10300efc8b.reward_long_sentences
  - rewards_ea3eddcc-601a-41d2-8206-6d10300efc8b.reward_low_unique_words_percentage
  - rewards_ea3eddcc-601a-41d2-8206-6d10300efc8b.reward_specific_char_count
  - rewards_ea3eddcc-601a-41d2-8206-6d10300efc8b.reward_reasoning_keywords
  reward_weights:
  - 7.497218460849231
  - 8.226554877896836
  - 3.445684706070964
  - 4.219093809550833
  - 2.4845571662551116
  temperature: 1.0
  use_vllm: false
trust_remote_code: true
val_set_size: 0.05
wandb_mode: online
wandb_name: ea3eddcc-601a-41d2-8206-6d10300efc8b
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: ea3eddcc-601a-41d2-8206-6d10300efc8b
warmup_steps: 100
weight_decay: 0.01
xformers_attention: false

39bc2fec-c9d4-4af9-9ced-88a0914c04a4

This model is a fine-tuned version of unsloth/codegemma-7b on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.8650

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: 0.0002
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 100
training_steps: 50

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.02	1	2.6118
2.1908	0.5	25	2.0237
1.8911	1.0	50	1.8650

Framework versions

PEFT 0.13.2
Transformers 4.46.0
Pytorch 2.5.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1