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surakarteh/
78bb3c80-1ad9-4bec-abbd-c40005fd85ee

Name: 78bb3c80-1ad9-4bec-abbd-c40005fd85ee
Availability: InStock

generated_from_trainer

TinyLlama/TinyLlama-1.1B-Chat-v0.6

adapter

apache-2.0

Views

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - bd01f0560d0132c8_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/bd01f0560d0132c8_train_data.json
  type:
    field_instruction: prompt
    field_output: GEITje-7B-ultra
    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: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: false
hub_model_id: surakarteh/78bb3c80-1ad9-4bec-abbd-c40005fd85ee
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 8.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.025
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 40
micro_batch_size: 8
mlflow_experiment_name: /tmp/bd01f0560d0132c8_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 4
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: 512
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: 2b37ef8d-5fad-470f-ba95-8ccbc60fe95f
wandb_project: Gradients-On-Demand
wandb_run: surakarteh
wandb_runid: 2b37ef8d-5fad-470f-ba95-8ccbc60fe95f
warmup_steps: 40
weight_decay: 0.03
xformers_attention: null

78bb3c80-1ad9-4bec-abbd-c40005fd85ee

This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v0.6 on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.0122

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: 8e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 128
optimizer: Use OptimizerNames.ADAMW_BNB 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: 40
training_steps: 40

Training results

Training Loss	Epoch	Step	Validation Loss
2.0563	0.0027	1	2.1161
2.1734	0.0081	3	2.1161
2.1254	0.0162	6	2.1157
2.0261	0.0243	9	2.1145
2.1204	0.0324	12	2.1118
2.0444	0.0406	15	2.1067
2.0855	0.0487	18	2.0982
2.0632	0.0568	21	2.0864
2.0524	0.0649	24	2.0730
2.043	0.0730	27	2.0608
1.9961	0.0811	30	2.0496
2.0964	0.0892	33	2.0377
2.0041	0.0973	36	2.0245
2.0591	0.1055	39	2.0122

Framework versions

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