metadata
library_name: peft
base_model: NousResearch/Yarn-Llama-2-13b-128k
tags:
- axolotl
- generated_from_trainer
model-index:
- name: d9afa13b-d57f-472f-a36a-50db151745e2
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: NousResearch/Yarn-Llama-2-13b-128k
bf16: true
chat_template: llama3
datasets:
- data_files:
- 17bd584d536d8764_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/17bd584d536d8764_train_data.json
type:
field_instruction: question
field_output: answer
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
hub_model_id: lesso08/d9afa13b-d57f-472f-a36a-50db151745e2
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
0: 77GiB
max_steps: 100
micro_batch_size: 8
mlflow_experiment_name: /tmp/17bd584d536d8764_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 25
save_strategy: steps
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: d9afa13b-d57f-472f-a36a-50db151745e2
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: d9afa13b-d57f-472f-a36a-50db151745e2
warmup_steps: 10
weight_decay: 0.01
xformers_attention: false
d9afa13b-d57f-472f-a36a-50db151745e2
This model is a fine-tuned version of NousResearch/Yarn-Llama-2-13b-128k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6998
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 10
- training_steps: 100
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.9392 | 0.0002 | 1 | 0.9574 |
1.8022 | 0.0017 | 9 | 0.9071 |
1.7202 | 0.0033 | 18 | 0.8204 |
1.5547 | 0.0050 | 27 | 0.7772 |
1.5276 | 0.0066 | 36 | 0.7516 |
1.5615 | 0.0083 | 45 | 0.7332 |
1.3978 | 0.0099 | 54 | 0.7208 |
1.4313 | 0.0116 | 63 | 0.7120 |
1.4247 | 0.0133 | 72 | 0.7056 |
1.3444 | 0.0149 | 81 | 0.7019 |
1.415 | 0.0166 | 90 | 0.7002 |
1.355 | 0.0182 | 99 | 0.6998 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1