See axolotl config
axolotl version: 0.4.1
base_model: meta-llama/Llama-3.2-3B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
# - path: anthracite-core/c2_logs_32k_mistral-v3_v1.2
# type: sharegpt
# conversation: chatml
- path: ./datasets/c2_deduped_32k_mistral-v3_tok_deanon_dsclean_1.2.jsonl
type: sharegpt
conversation: chatml
# - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
# type: sharegpt
# conversation: chatml
- path: ./datasets/opus-instruct-22k-no_refusals.jsonl
type: sharegpt
conversation: chatml
# - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
# type: sharegpt
# conversation: chatml
- path: ./datasets/kalo-3k-filtered.jsonl
type: sharegpt
conversation: chatml
# - path: anthracite-org/nopm_claude_writing_fixed
# type: sharegpt
# conversation: chatml
- path: ./datasets/claudewritingNopm.jsonl
type: sharegpt
conversation: chatml
# - path: anthracite-org/kalo_opus_misc_240827
# type: sharegpt
# conversation: chatml
- path: ./datasets/kalo_opus_misc_240827.jsonl
type: sharegpt
conversation: chatml
# - path: anthracite-org/kalo_misc_part2
# type: sharegpt
# conversation: chatml
- path: ./datasets/kalo_misc_part2.jsonl
type: sharegpt
conversation: chatml
# - path: NewEden/Claude-Instruct-5K
# type: sharegpt
# conversation: chatml
- path: ./datasets/5k.jsonl
type: sharegpt
conversation: chatml
#chat_template: chatml
shuffle_merged_datasets: true
#default_system_message: "You are an assistant that responds to the user."
dataset_prepared_path: ./magnum-22b-data
val_set_size: 0.0
output_dir: ./22b-fft-out
sequence_len: 16000
sample_packing: true
pad_to_sequence_len: true
wandb_project: 3bmagnum
wandb_entity:
wandb_watch:
wandb_name: 3magnum
wandb_log_model:
gradient_accumulation_steps: 32
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000005
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 40
evals_per_epoch:
eval_table_size:
eval_max_new_tokens:
saves_per_epoch: 2
debug:
#deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
weight_decay: 0.01
fsdp:
fsdp_config:
special_tokens:
pad_token: <|finetune_right_pad_id|>
22b-fft-out
This model is a fine-tuned version of meta-llama/Llama-3.2-3B on the None dataset.
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: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 40
- num_epochs: 2
Training results
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Edens-Gate/Holland-3b
Base model
meta-llama/Llama-3.2-3B