|
--- |
|
library_name: peft |
|
base_model: NousResearch/Yarn-Llama-2-7b-128k |
|
tags: |
|
- axolotl |
|
- generated_from_trainer |
|
model-index: |
|
- name: a8875a95-a87f-4fb5-a7c2-215272809544 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
|
<details><summary>See axolotl config</summary> |
|
|
|
axolotl version: `0.4.1` |
|
```yaml |
|
adapter: lora |
|
base_model: NousResearch/Yarn-Llama-2-7b-128k |
|
bf16: auto |
|
chat_template: llama3 |
|
cosine_min_lr_ratio: 0.1 |
|
data_processes: 4 |
|
dataset_prepared_path: null |
|
datasets: |
|
- data_files: |
|
- 536825f84ab6c1ab_train_data.json |
|
ds_type: json |
|
format: custom |
|
num_proc: 4 |
|
path: /workspace/input_data/536825f84ab6c1ab_train_data.json |
|
streaming: true |
|
type: |
|
field_instruction: instruction |
|
field_output: output |
|
format: '{instruction}' |
|
no_input_format: '{instruction}' |
|
system_format: '{system}' |
|
system_prompt: '' |
|
debug: null |
|
deepspeed: null |
|
device_map: balanced |
|
do_eval: true |
|
early_stopping_patience: 1 |
|
eval_batch_size: 1 |
|
eval_sample_packing: false |
|
eval_steps: 25 |
|
evaluation_strategy: steps |
|
flash_attention: false |
|
fp16: null |
|
fsdp: null |
|
fsdp_config: null |
|
gradient_accumulation_steps: 16 |
|
gradient_checkpointing: true |
|
group_by_length: true |
|
hub_model_id: eeeebbb2/a8875a95-a87f-4fb5-a7c2-215272809544 |
|
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: 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 |
|
- v_proj |
|
lr_scheduler: cosine |
|
max_grad_norm: 1.0 |
|
max_memory: |
|
0: 75GB |
|
1: 75GB |
|
2: 75GB |
|
3: 75GB |
|
max_steps: 50 |
|
micro_batch_size: 2 |
|
mixed_precision: bf16 |
|
mlflow_experiment_name: /tmp/536825f84ab6c1ab_train_data.json |
|
model_type: AutoModelForCausalLM |
|
num_epochs: 3 |
|
optim_args: |
|
adam_beta1: 0.9 |
|
adam_beta2: 0.95 |
|
adam_epsilon: 1e-5 |
|
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: 2048 |
|
strict: false |
|
tf32: false |
|
tokenizer_type: AutoTokenizer |
|
torch_compile: false |
|
train_on_inputs: false |
|
trust_remote_code: true |
|
val_set_size: 50 |
|
wandb_entity: null |
|
wandb_mode: online |
|
wandb_name: a8875a95-a87f-4fb5-a7c2-215272809544 |
|
wandb_project: Public_TuningSN |
|
wandb_runid: a8875a95-a87f-4fb5-a7c2-215272809544 |
|
warmup_ratio: 0.04 |
|
weight_decay: 0.01 |
|
xformers_attention: null |
|
|
|
``` |
|
|
|
</details><br> |
|
|
|
# a8875a95-a87f-4fb5-a7c2-215272809544 |
|
|
|
This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-7b-128k](https://huggingface.co/NousResearch/Yarn-Llama-2-7b-128k) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5879 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 128 |
|
- total_eval_batch_size: 4 |
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 2 |
|
- training_steps: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 25.6742 | 0.0025 | 1 | 2.1383 | |
|
| 29.4658 | 0.0623 | 25 | 1.6877 | |
|
| 26.3377 | 0.1246 | 50 | 1.5879 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.13.2 |
|
- Transformers 4.46.0 |
|
- Pytorch 2.5.0+cu124 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.20.1 |
