base_model: NousResearch/Hermes-3-Llama-3.1-70B
library_name: peft
license: llama3
tags:
- generated_from_trainer
model-index: - name: outputs/out/Hermes-3-Llama-3.1-70B-Uncensored
results: []
See axolotl config
axolotl version: 0.4.1
base_model: NousResearch/Hermes-3-Llama-3.1-70B
tokenizer_type: AutoTokenizer
load_in_4bit: true
strict: false
datasets:
- path: Guilherme34/uncensor
type: chat_template
chat_template: llama3
field_messages: messages
message_field_role: role
message_field_content: content
roles:
system:
- system
user:
- user
assistant:
- assistant
dataset_prepared_path: last_run_prepared
val_set_size: 0.0
output_dir: ./outputs/out/Hermes-3-Llama-3.1-70B-Uncensored
save_safetensors: true
adapter: qlora
sequence_len: 2048
sample_packing: true
pad_to_sequence_len: true
lora_r: 16
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.00001
train_on_inputs: false
group_by_length: false
bf16: true
tf32: true
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
logging_steps: 1
flash_attention: true
warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
weight_decay: 0.0
fsdp:
- full_shard
- auto_wrap
fsdp_config:
fsdp_limit_all_gathers: true
fsdp_sync_module_states: true
fsdp_offload_params: true
fsdp_use_orig_params: false
fsdp_cpu_ram_efficient_loading: true
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
fsdp_state_dict_type: FULL_STATE_DICT
fsdp_sharding_strategy: FULL_SHARD
special_tokens:
pad_token: <|finetune_right_pad_id|>
outputs/out/Hermes-3-Llama-3.1-70B-Uncensored
This model is a fine-tuned version of NousResearch/Hermes-3-Llama-3.1-70B 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 10
- num_epochs: 4
Training results
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1