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eddysang/4ebfb258-edc4-4a06-9f79-9cc8fd87c956
4ebfb258-edc4-4a06-9f79-9cc8fd87c956 is a machine learning model from eddysang. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as llama3.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: Orenguteng/Llama-3-8B-Lexi-Uncensored
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- a48c142240d02e44_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/a48c142240d02e44_train_data.json
type:
field_instruction: prompt
field_output: reference_response
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 256
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 32
gradient_checkpointing: true
group_by_length: false
hub_model_id: eddysang/4ebfb258-edc4-4a06-9f79-9cc8fd87c956
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 3
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 2
max_steps: 100
micro_batch_size: 2
mlflow_experiment_name: /tmp/a48c142240d02e44_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optim_args:
adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 1.0e-05
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 2048
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: yaudayah0
wandb_mode: online
wandb_name: 78856a4f-d444-44d0-836a-8c222d003003
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 78856a4f-d444-44d0-836a-8c222d003003
warmup_steps: 20
weight_decay: 0.02
xformers_attention: false
</details><br>
This model is a fine-tuned version of Orenguteng/Llama-3-8B-Lexi-Uncensored on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0013 | 1 | 0.8664 |
| 0.7357 | 0.0117 | 9 | 0.7832 |
| 0.6626 | 0.0235 | 18 | 0.7076 |
| 0.6482 | 0.0352 | 27 | 0.6773 |
| 0.6226 | 0.0470 | 36 | 0.6609 |
| 0.6341 | 0.0587 | 45 | 0.6502 |
| 0.6321 | 0.0704 | 54 | 0.6437 |
| 0.6153 | 0.0822 | 63 | 0.6389 |
| 0.6146 | 0.0939 | 72 | 0.6340 |
| 0.5741 | 0.1057 | 81 | 0.6318 |
| 0.5841 | 0.1174 | 90 | 0.6305 |
| 0.5812 | 0.1291 | 99 | 0.6302 |