library_name: peft
tags:
- axolotl
- base_model:adapter:art-from-the-machine/Mantella-Skyrim-Llama-3-8B
- lora
- transformers
datasets: - ICEPVP8977/Uncensored_Small_Reasoning
pipeline_tag: text-generation
base_model: art-from-the-machine/Mantella-Skyrim-Llama-3-8B
model-index: - name: Mantella-Skyrim-Llama-3-8B-Uncensored-Lora
results: []
See axolotl config
axolotl version: 0.12.0.dev0
base_model: /pool16_2/Mantella-Skyrim-Llama-3-8B
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
# for use with fft to only train on language model layers
# unfrozen_parameters:
# - model.language_model.*
# - lm_head
# - embed_tokens
load_in_8bit: false
load_in_4bit: false
# these 3 lines are needed for now to handle vision chat templates w images
#skip_prepare_dataset: true
#remove_unused_columns: false
#sample_packing: false
# gemma3 doesn't seem to play nice with ddp
#ddp_find_unused_parameters: true
chat_template: llama3
datasets:
- path: /root/Uncensored_Reasoner_Small_Chat.json
type: chat_template
field_messages: messages
dataset_prepared_path: last_run_prepared_Mantella-Skyrim-Llama-3-8B-uncensored_final
val_set_size: 0.01
output_dir: ./HDD/Mantella-Skyrim-Llama-3-8B-uncensored_final
adapter: lora
# lora_model_dir:
peft_use_rslora: true
sequence_len: 5400
pad_to_sequence_len: false
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
gradient_accumulation_steps: 1
micro_batch_size: 2
num_epochs: 8
optimizer: adamw_torch_fused
lr_scheduler: cosine
learning_rate: 0.00004
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
auto_resume_from_checkpoints: true
logging_steps: 1
flash_attention: true
#eager_attention: true
warmup_steps: 50
evals_per_epoch: 2
eval_max_new_tokens: 128
saves_per_epoch: 2
save_total_limit: 100
debug:
weight_decay: 0.0
deepspeed: deepspeed_configs/zero1.json
special_tokens:
pad_token: <|end_of_text|>
HDD/Mantella-Skyrim-Llama-3-8B-uncensored_final
This model was trained from scratch on the /root/Uncensored_Reasoner_Small_Chat.json dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1322
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: 4e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 50
- training_steps: 4495
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0 | 0 | 1.8614 |
| 1.0431 | 0.5 | 281 | 1.1419 |
| 1.206 | 1.0 | 562 | 1.0708 |
| 1.061 | 1.5 | 843 | 1.0362 |
| 0.7878 | 2.0 | 1124 | 1.0065 |
| 0.8042 | 2.5 | 1405 | 0.9940 |
| 0.673 | 3.0 | 1686 | 0.9824 |
| 0.6364 | 3.5 | 1967 | 1.0085 |
| 0.5152 | 4.0 | 2248 | 0.9915 |
| 0.4905 | 4.5 | 2529 | 1.0410 |
| 0.5221 | 5.0 | 2810 | 1.0166 |
| 0.2905 | 5.5 | 3091 | 1.0783 |
| 0.3028 | 6.0 | 3372 | 1.0636 |
| 0.2572 | 6.5 | 3653 | 1.1089 |
| 0.3408 | 7.0 | 3934 | 1.1059 |
| 0.2769 | 7.5 | 4215 | 1.1322 |
Framework versions
- PEFT 0.16.0
- Transformers 4.53.2
- Pytorch 2.7.1+cu128
- Datasets 4.0.0
- Tokenizers 0.21.2