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VERSIL91/
257830ec-f9da-4f7c-a257-4825b5a789ce

Name: 257830ec-f9da-4f7c-a257-4825b5a789ce
Availability: InStock

generated_from_trainer

unsloth/SmolLM2-360M

adapter

apache-2.0

Views

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: unsloth/SmolLM2-360M
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 489ba0c0b517eaf7_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/489ba0c0b517eaf7_train_data.json
  type:
    field_instruction: intent
    field_output: example
    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: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: null
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
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_steps: 100
micro_batch_size: 8
mlflow_experiment_name: /tmp/489ba0c0b517eaf7_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
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: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: techspear-hub
wandb_mode: online
wandb_name: 05ecb6f6-029b-4441-9ec9-65299a737077
wandb_project: Gradients-On-Two
wandb_run: your_name
wandb_runid: 05ecb6f6-029b-4441-9ec9-65299a737077
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

0d8f1810-af0c-4b52-973f-9fe030a29e08

This model is a fine-tuned version of unsloth/SmolLM2-360M on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.5380

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
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: 100

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0023	1	5.7676
5.7661	0.0209	9	5.7401
5.2717	0.0419	18	5.5136
5.1694	0.0628	27	5.0614
4.6917	0.0837	36	4.5808
4.1217	0.1047	45	4.1795
3.8083	0.1256	54	3.9013
3.6188	0.1465	63	3.7237
3.654	0.1674	72	3.6171
3.4858	0.1884	81	3.5632
3.5462	0.2093	90	3.5419
3.4723	0.2302	99	3.5380

Framework versions

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

VERSIL91/257830ec-f9da-4f7c-a257-4825b5a789ce

0d8f1810-af0c-4b52-973f-9fe030a29e08

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

VERSIL91/
257830ec-f9da-4f7c-a257-4825b5a789ce