See axolotl config
axolotl version: 0.4.1
# Experiment goal: are the representations diverse enough with just annotation on a variety of input texts?
base_model: meta-llama/Meta-Llama-3-8B
# Heralax/bittensor-mistral-pretrained-base-1
#mistralai/Mistral-7B-v0.1
# Heralax/bittensor-mistral-pretrained-base-1
#mistralai/Mistral-7B-v0.1
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
is_mistral_derived_model: false
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: json
data_files: ./essays_annotation_syspromptvaried.jsonl
ds_type: json
type: sharegpt
conversation: chatml
- path: json
data_files: ./tweets_annotation_syspromptvaried.jsonl
ds_type: json
type: sharegpt
conversation: chatml
- path: json
data_files: ./autometa_4_percent.json
ds_type: json
type: sharegpt
conversation: chatml
# - path: json
# data_files: paul_graham_essays_completion.json
# ds_type: json
# type: completion
dataset_prepared_path: last_run_prepared
output_dir: ./paulgraham-finetune-out
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
shuffle_merged_datasets: true
wandb_project: pg-test
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:
gradient_accumulation_steps: 6
micro_batch_size: 2
eval_batch_size: 1
num_epochs: 7
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.000024
weight_decay: 0
# Gradient clipping max norm
max_grad_norm: 1.0
noisy_embedding_alpha: 0
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: unsloth
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
# fsdp:
# - full_shard
# - auto_wrap
# fsdp_config:
# fsdp_offload_params: false
# fsdp_state_dict_type: FULL_STATE_DICT
# fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
# warmup_steps: 10
warmup_ratio: 0.5
auto_resume_from_checkpoints: false
#warmup_ratio: 0.5
eval_steps: 10
saves_per_epoch: 1
eval_sample_packing: false
save_total_limit: 2
debug:
deepspeed: deepspeed_configs/zero2.json
chat_template: chatml
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"
pad_token: "</s>"
paulgraham-finetune-out
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B 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: 2.4e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 6
- total_train_batch_size: 72
- total_eval_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 31
- num_epochs: 7
Training results
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Heralax/llama-3-paulgraham-2-no-special-tokens
Base model
meta-llama/Meta-Llama-3-8B