---
library_name: peft
license: apache-2.0
base_model: unsloth/tinyllama-chat
tags:
- axolotl
- generated_from_trainer
model-index:
- name: bff63b9e-7f53-41d9-8f9a-349f2381339d
results: []
---
[](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config
axolotl version: `0.5.2`
```yaml
adapter: lora
base_model: unsloth/tinyllama-chat
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- b18e8d5dfa1d6d34_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/b18e8d5dfa1d6d34_train_data.json
type:
field_instruction: question
field_output: output
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 25
eval_table_size: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: true
hub_model_id: Rodo-Sami/bff63b9e-7f53-41d9-8f9a-349f2381339d
hub_repo: null
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
lr_scheduler: cosine
max_steps: 50
micro_batch_size: 2
mlflow_experiment_name: /tmp/b18e8d5dfa1d6d34_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
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
sequence_len: 2048
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: disabled
wandb_name: bff63b9e-7f53-41d9-8f9a-349f2381339d
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: bff63b9e-7f53-41d9-8f9a-349f2381339d
warmup_ratio: 0.05
weight_decay: 0.01
xformers_attention: true
```
# bff63b9e-7f53-41d9-8f9a-349f2381339d
This model is a fine-tuned version of [unsloth/tinyllama-chat](https://huggingface.co/unsloth/tinyllama-chat) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2592
## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 2
- training_steps: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8853 | 0.0013 | 1 | 2.9229 |
| 1.7674 | 0.0331 | 25 | 1.3550 |
| 1.5912 | 0.0662 | 50 | 1.2592 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.3.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3