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dimasik2987/
f8ab9945-9dbd-4d10-8b1a-d03de77f8983

Name: f8ab9945-9dbd-4d10-8b1a-d03de77f8983
Availability: InStock

generated_from_trainer

TinyLlama/TinyLlama-1.1B-Chat-v1.0

adapter

apache-2.0

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - d7df0fdb451d4fa1_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/d7df0fdb451d4fa1_train_data.json
  type:
    field_instruction: instruction
    field_output: output
    format: '{instruction}'
    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: 3
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: dimasik2987/f8ab9945-9dbd-4d10-8b1a-d03de77f8983
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: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 70GiB
max_steps: 25
micro_batch_size: 4
mlflow_experiment_name: /tmp/d7df0fdb451d4fa1_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 25
save_strategy: steps
sequence_len: 4056
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: f8ab9945-9dbd-4d10-8b1a-d03de77f8983
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: f8ab9945-9dbd-4d10-8b1a-d03de77f8983
warmup_ratio: 0.05
weight_decay: 0.01
xformers_attention: null

f8ab9945-9dbd-4d10-8b1a-d03de77f8983

This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.2043

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 2
training_steps: 25

Training results

Training Loss	Epoch	Step	Validation Loss
1.1508	0.0007	1	1.2968
1.1669	0.0020	3	1.2535
1.3216	0.0039	6	1.2274
1.3049	0.0059	9	1.2163
1.2819	0.0078	12	1.2117
1.2237	0.0098	15	1.2084
1.2384	0.0118	18	1.2060
1.154	0.0137	21	1.2047
1.1718	0.0157	24	1.2043

Framework versions

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