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---
library_name: peft
base_model: The-matt/llama2_ko-7b_distinctive-snowflake-182_1060
tags:
- axolotl
- generated_from_trainer
model-index:
- name: b6c0f5de-55f2-4ac6-8874-b64ce6ab339d
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: The-matt/llama2_ko-7b_distinctive-snowflake-182_1060
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 18a14ece5e7e4289_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/18a14ece5e7e4289_train_data.json
type:
field_input: reviews
field_instruction: prompt
field_output: response_0
format: '{instruction} {input}'
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: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: leixa/b6c0f5de-55f2-4ac6-8874-b64ce6ab339d
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
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_steps: 200
micro_batch_size: 8
mlflow_experiment_name: /tmp/18a14ece5e7e4289_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
saves_per_epoch: 4
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: techspear-hub
wandb_mode: online
wandb_name: dd900796-f963-4175-96f7-d01fc47c8c9a
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: dd900796-f963-4175-96f7-d01fc47c8c9a
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# b6c0f5de-55f2-4ac6-8874-b64ce6ab339d
This model is a fine-tuned version of [The-matt/llama2_ko-7b_distinctive-snowflake-182_1060](https://huggingface.co/The-matt/llama2_ko-7b_distinctive-snowflake-182_1060) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9086
## 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: 4
- total_train_batch_size: 32
- 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
- training_steps: 200
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log | 0.0135 | 1 | 1.4551 |
| 1.3167 | 0.2297 | 17 | 1.2300 |
| 1.1556 | 0.4595 | 34 | 1.0813 |
| 1.053 | 0.6892 | 51 | 1.0124 |
| 1.0243 | 0.9189 | 68 | 0.9729 |
| 0.9503 | 1.1486 | 85 | 0.9501 |
| 0.9288 | 1.3784 | 102 | 0.9384 |
| 0.8869 | 1.6081 | 119 | 0.9246 |
| 0.8928 | 1.8378 | 136 | 0.9162 |
| 0.8476 | 2.0676 | 153 | 0.9106 |
| 0.8626 | 2.2973 | 170 | 0.9093 |
| 0.8269 | 2.5270 | 187 | 0.9086 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1