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romainnn/
8e00cdc6-d862-4712-b13f-4cecaa5176e0

Name: 8e00cdc6-d862-4712-b13f-4cecaa5176e0
Availability: InStock

generated_from_trainer

jhflow/mistral7b-lora-multi-turn-v2

adapter

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: jhflow/mistral7b-lora-multi-turn-v2
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 58d3ffff44627e8e_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/58d3ffff44627e8e_train_data.json
  type:
    field_instruction: dialogue
    field_output: summary
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 2
early_stopping_threshold: 0.0001
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: romainnn/8e00cdc6-d862-4712-b13f-4cecaa5176e0
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.3
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 409
micro_batch_size: 4
mlflow_experiment_name: /tmp/58d3ffff44627e8e_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 2048
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: online
wandb_name: d7cc8030-b22e-48df-a9c7-a9b6195392f1
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: d7cc8030-b22e-48df-a9c7-a9b6195392f1
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

8e00cdc6-d862-4712-b13f-4cecaa5176e0

This model is a fine-tuned version of jhflow/mistral7b-lora-multi-turn-v2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7430

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_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: 10
training_steps: 409

Training results

Training Loss	Epoch	Step	Validation Loss
12.9001	0.0022	1	1.5329
6.85	0.2192	100	0.8857
6.6707	0.4384	200	0.8193
5.5822	0.6575	300	0.7648
5.7335	0.8767	400	0.7430

Framework versions

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