---
library_name: peft
license: other
base_model: facebook/opt-350m
tags:
- axolotl
- generated_from_trainer
model-index:
- name: bab80e07-cf92-4525-abe6-bf0d64212509
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-350m
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
- 9b3a5919e996b43f_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/9b3a5919e996b43f_train_data.json
type:
field_input: thinking
field_instruction: prompt
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: 100
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: true
hub_model_id: error577/bab80e07-cf92-4525-abe6-bf0d64212509
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: null
micro_batch_size: 2
mlflow_experiment_name: /tmp/9b3a5919e996b43f_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch_4bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.005
wandb_entity: null
wandb_mode: online
wandb_name: ef00d239-571d-44fb-ae4b-a020df7f09b1
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: ef00d239-571d-44fb-ae4b-a020df7f09b1
warmup_steps: 30
weight_decay: 0.0
xformers_attention: null
```
# bab80e07-cf92-4525-abe6-bf0d64212509
This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6809
## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_4BIT 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: 30
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log | 0.0005 | 1 | 1.7855 |
| 5.1691 | 0.0537 | 100 | 1.2518 |
| 4.7876 | 0.1075 | 200 | 1.1656 |
| 4.3157 | 0.1612 | 300 | 1.0780 |
| 4.2875 | 0.2150 | 400 | 1.0325 |
| 4.4765 | 0.2687 | 500 | 0.9903 |
| 4.1246 | 0.3225 | 600 | 0.9688 |
| 3.8197 | 0.3762 | 700 | 0.9726 |
| 3.8941 | 0.4300 | 800 | 0.9635 |
| 4.1191 | 0.4837 | 900 | 0.9212 |
| 3.6611 | 0.5375 | 1000 | 0.9328 |
| 3.5027 | 0.5912 | 1100 | 0.8896 |
| 3.4397 | 0.6450 | 1200 | 0.9109 |
| 3.5156 | 0.6987 | 1300 | 0.8761 |
| 3.7601 | 0.7525 | 1400 | 0.8751 |
| 3.4886 | 0.8062 | 1500 | 0.8606 |
| 3.1389 | 0.8600 | 1600 | 0.8488 |
| 3.2549 | 0.9137 | 1700 | 0.8776 |
| 3.4852 | 0.9675 | 1800 | 0.8418 |
| 3.3517 | 1.0212 | 1900 | 0.8019 |
| 3.1547 | 1.0750 | 2000 | 0.8292 |
| 3.1288 | 1.1287 | 2100 | 0.7916 |
| 2.9624 | 1.1825 | 2200 | 0.8047 |
| 3.1523 | 1.2362 | 2300 | 0.7841 |
| 3.01 | 1.2900 | 2400 | 0.7736 |
| 3.2158 | 1.3437 | 2500 | 0.7726 |
| 3.0904 | 1.3975 | 2600 | 0.7758 |
| 2.9655 | 1.4512 | 2700 | 0.7682 |
| 3.1154 | 1.5050 | 2800 | 0.7612 |
| 3.199 | 1.5587 | 2900 | 0.7508 |
| 3.1015 | 1.6125 | 3000 | 0.7463 |
| 2.9626 | 1.6662 | 3100 | 0.7425 |
| 3.0086 | 1.7200 | 3200 | 0.7358 |
| 2.9609 | 1.7737 | 3300 | 0.7343 |
| 2.7884 | 1.8275 | 3400 | 0.7286 |
| 2.9546 | 1.8812 | 3500 | 0.7227 |
| 2.8298 | 1.9350 | 3600 | 0.7203 |
| 2.8598 | 1.9887 | 3700 | 0.7133 |
| 2.5154 | 2.0425 | 3800 | 0.7121 |
| 2.6962 | 2.0962 | 3900 | 0.7085 |
| 2.7309 | 2.1500 | 4000 | 0.7024 |
| 2.6869 | 2.2037 | 4100 | 0.7035 |
| 2.7636 | 2.2575 | 4200 | 0.6971 |
| 2.7232 | 2.3112 | 4300 | 0.6901 |
| 2.8095 | 2.3650 | 4400 | 0.6923 |
| 2.725 | 2.4187 | 4500 | 0.6882 |
| 2.793 | 2.4725 | 4600 | 0.6892 |
| 2.6342 | 2.5262 | 4700 | 0.6852 |
| 2.8126 | 2.5800 | 4800 | 0.6832 |
| 2.4884 | 2.6337 | 4900 | 0.6812 |
| 2.6875 | 2.6874 | 5000 | 0.6800 |
| 2.7025 | 2.7412 | 5100 | 0.6811 |
| 2.6606 | 2.7949 | 5200 | 0.6808 |
| 2.5986 | 2.8487 | 5300 | 0.6809 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1