Heralax/llama-3-paulgraham-2-no-special-tokens

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