---
library_name: peft
license: other
base_model: facebook/opt-125m
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 5f0159c4-1008-4527-9092-4ee6e6b9e663
results: []
---
[
](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config
axolotl version: `0.4.1`
```yaml
adapter: qlora
auto_resume_from_checkpoints: true
base_model: facebook/opt-125m
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
- 47b36a24df61e9c5_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/47b36a24df61e9c5_train_data.json
type:
field_input: documents
field_instruction: question
field_output: answer
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: true
hub_model_id: error577/5f0159c4-1008-4527-9092-4ee6e6b9e663
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0003
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.3
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 128
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: null
micro_batch_size: 1
mlflow_experiment_name: /tmp/47b36a24df61e9c5_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 50
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.02
wandb_entity: null
wandb_mode: online
wandb_name: a6924886-18eb-47b1-8a4b-24becc99648c
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: a6924886-18eb-47b1-8a4b-24becc99648c
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null
```
# 5f0159c4-1008-4527-9092-4ee6e6b9e663
This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2857
## 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: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_BNB 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
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 47.7848 | 0.0004 | 1 | 3.0276 |
| 34.159 | 0.0202 | 50 | 2.9019 |
| 39.2367 | 0.0405 | 100 | 2.5922 |
| 52.0151 | 0.0607 | 150 | 2.5356 |
| 33.4878 | 0.0809 | 200 | 2.5099 |
| 25.6957 | 0.1012 | 250 | 2.4814 |
| 27.5454 | 0.1214 | 300 | 2.4519 |
| 32.6855 | 0.1417 | 350 | 2.4207 |
| 25.3411 | 0.1619 | 400 | 2.4211 |
| 27.4427 | 0.1821 | 450 | 2.4128 |
| 34.6101 | 0.2024 | 500 | 2.3944 |
| 23.8259 | 0.2226 | 550 | 2.3888 |
| 23.7378 | 0.2428 | 600 | 2.3808 |
| 27.431 | 0.2631 | 650 | 2.3735 |
| 26.069 | 0.2833 | 700 | 2.3755 |
| 20.5981 | 0.3035 | 750 | 2.3722 |
| 23.1821 | 0.3238 | 800 | 2.3646 |
| 20.5374 | 0.3440 | 850 | 2.3509 |
| 22.8665 | 0.3642 | 900 | 2.3556 |
| 21.9577 | 0.3845 | 950 | 2.3418 |
| 20.0986 | 0.4047 | 1000 | 2.3399 |
| 29.616 | 0.4250 | 1050 | 2.3433 |
| 25.8536 | 0.4452 | 1100 | 2.3335 |
| 18.732 | 0.4654 | 1150 | 2.3298 |
| 21.2083 | 0.4857 | 1200 | 2.3250 |
| 20.2594 | 0.5059 | 1250 | 2.3195 |
| 14.3002 | 0.5261 | 1300 | 2.3196 |
| 24.714 | 0.5464 | 1350 | 2.3132 |
| 22.0257 | 0.5666 | 1400 | 2.3093 |
| 16.7176 | 0.5868 | 1450 | 2.3012 |
| 15.5525 | 0.6071 | 1500 | 2.3052 |
| 20.5451 | 0.6273 | 1550 | 2.2970 |
| 31.716 | 0.6475 | 1600 | 2.2905 |
| 23.2587 | 0.6678 | 1650 | 2.2938 |
| 16.72 | 0.6880 | 1700 | 2.2914 |
| 19.7095 | 0.7083 | 1750 | 2.2868 |
| 25.7639 | 0.7285 | 1800 | 2.2802 |
| 30.8813 | 0.7487 | 1850 | 2.2860 |
| 25.8737 | 0.7690 | 1900 | 2.2825 |
| 21.8546 | 0.7892 | 1950 | 2.2857 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1