Rodo-Sami/46207b3d-8f8d-4c3c-abc9-9584b1d558f6
013
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>
axolotl version: 0.6.0
adapter: lora
base_model: unsloth/gemma-2-2b-it
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 8f45cd632fa1120d_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/8f45cd632fa1120d_train_data.json
type:
field_input: thinking
field_instruction: prompt
field_output: answer
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: false
group_by_length: true
hub_model_id: Rodo-Sami/46207b3d-8f8d-4c3c-abc9-9584b1d558f6
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
0: 75GB
max_steps: 1500
micro_batch_size: 2
mlflow_experiment_name: /tmp/8f45cd632fa1120d_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optim_args:
adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 1e-5
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 1024
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: offline
wandb_name: 1254f0ce-e179-4756-bb5c-7b446f52c4ac
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 1254f0ce-e179-4756-bb5c-7b446f52c4ac
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
</details><br>
46207b3d-8f8d-4c3c-abc9-9584b1d558f6
This model is a fine-tuned version of unsloth/gemma-2-2b-it on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9580
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
- trainbatchsize: 2
- evalbatchsize: 2
- seed: 42
- gradientaccumulationsteps: 8
- totaltrainbatch_size: 16
- optimizer: Use adamwbnb8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=adambeta1=0.9,adambeta2=0.95,adamepsilon=1e-5
- lrschedulertype: cosine
- lrschedulerwarmup_steps: 10
- training_steps: 936
Training results
Framework versions
- PEFT 0.14.0
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3