---
library_name: peft
license: llama3
base_model: aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: f012b85a-9c1b-469f-b4eb-57c9380d9c2c
results: []
---
[
](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config
axolotl version: `0.4.1`
```yaml
adapter: lora
auto_find_batch_size: true
base_model: aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- c0bbe39ceb13871b_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/c0bbe39ceb13871b_train_data.json
type:
field_input: full_label
field_instruction: label
field_output: text
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
group_by_length: true
hub_model_id: lesso13/f012b85a-9c1b-469f-b4eb-57c9380d9c2c
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.000213
load_in_4bit: false
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: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/G.O.D/c0bbe39ceb13871b_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
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
saves_per_epoch: null
sequence_len: 512
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 0e0efa1d-335c-42c5-811f-ba1deee68e7e
wandb_project: 13a
wandb_run: your_name
wandb_runid: 0e0efa1d-335c-42c5-811f-ba1deee68e7e
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null
```
# f012b85a-9c1b-469f-b4eb-57c9380d9c2c
This model is a fine-tuned version of [aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct](https://huggingface.co/aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9449
## 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: 0.000213
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 50
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log | 0.0015 | 1 | 2.5286 |
| 2.2357 | 0.0726 | 50 | 2.3870 |
| 2.1284 | 0.1451 | 100 | 2.3372 |
| 2.0528 | 0.2177 | 150 | 2.1948 |
| 2.0656 | 0.2903 | 200 | 2.1229 |
| 2.0311 | 0.3628 | 250 | 2.0805 |
| 1.9881 | 0.4354 | 300 | 2.0402 |
| 1.9632 | 0.5080 | 350 | 1.9960 |
| 1.8051 | 0.5806 | 400 | 1.9633 |
| 1.889 | 0.6531 | 450 | 1.9480 |
| 1.8717 | 0.7257 | 500 | 1.9449 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1