---
library_name: peft
license: apache-2.0
base_model: unsloth/tinyllama-chat
tags:
- axolotl
- generated_from_trainer
model-index:
- name: b2d8d09c-2fec-4b71-97a6-bc2a5685c8f7
  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
auto_find_batch_size: true
base_model: unsloth/tinyllama-chat
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
  - 6f716a15529b2fe2_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/6f716a15529b2fe2_train_data.json
  type:
    field_input: proposition
    field_instruction: instruction
    field_output: response
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
early_stopping_threshold: 0.0001
eval_max_new_tokens: 128
eval_steps: 114
eval_strategy: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
group_by_length: false
hub_model_id: mrferr3t/b2d8d09c-2fec-4b71-97a6-bc2a5685c8f7
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0004
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 114
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_steps: 
micro_batch_size: 32
mlflow_experiment_name: /tmp/6f716a15529b2fe2_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 100
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: 
s2_attention: null
sample_packing: false
save_steps: 114
saves_per_epoch: 0
sequence_len: 512
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: 
wandb_name: 4ff326cf-471d-4d59-ae36-92a16644d352
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 4ff326cf-471d-4d59-ae36-92a16644d352
warmup_steps: 100
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# b2d8d09c-2fec-4b71-97a6-bc2a5685c8f7

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: 0.7085

## 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: 0.0004
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 100
- num_epochs: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0004 | 1    | 1.2216          |
| 1.0283        | 0.0476 | 114  | 0.9294          |
| 0.8867        | 0.0953 | 228  | 0.8753          |
| 0.8604        | 0.1429 | 342  | 0.8479          |
| 0.8315        | 0.1905 | 456  | 0.8264          |
| 0.8176        | 0.2381 | 570  | 0.8114          |
| 0.7998        | 0.2858 | 684  | 0.7996          |
| 0.7906        | 0.3334 | 798  | 0.7886          |
| 0.7806        | 0.3810 | 912  | 0.7824          |
| 0.777         | 0.4287 | 1026 | 0.7745          |
| 0.7707        | 0.4763 | 1140 | 0.7686          |
| 0.7659        | 0.5239 | 1254 | 0.7642          |
| 0.7638        | 0.5715 | 1368 | 0.7571          |
| 0.7561        | 0.6192 | 1482 | 0.7543          |
| 0.7521        | 0.6668 | 1596 | 0.7510          |
| 0.7468        | 0.7144 | 1710 | 0.7476          |
| 0.7471        | 0.7621 | 1824 | 0.7433          |
| 0.7413        | 0.8097 | 1938 | 0.7407          |
| 0.7385        | 0.8573 | 2052 | 0.7358          |
| 0.7286        | 0.9050 | 2166 | 0.7352          |
| 0.7323        | 0.9526 | 2280 | 0.7323          |
| 0.7328        | 1.0002 | 2394 | 0.7303          |
| 0.6772        | 1.0478 | 2508 | 0.7296          |
| 0.6772        | 1.0955 | 2622 | 0.7296          |
| 0.6746        | 1.1431 | 2736 | 0.7292          |
| 0.682         | 1.1907 | 2850 | 0.7256          |
| 0.69          | 1.2384 | 2964 | 0.7252          |
| 0.6872        | 1.2860 | 3078 | 0.7244          |
| 0.6921        | 1.3336 | 3192 | 0.7218          |
| 0.6872        | 1.3812 | 3306 | 0.7193          |
| 0.686         | 1.4289 | 3420 | 0.7186          |
| 0.6857        | 1.4765 | 3534 | 0.7161          |
| 0.6834        | 1.5241 | 3648 | 0.7160          |
| 0.6831        | 1.5718 | 3762 | 0.7150          |
| 0.6892        | 1.6194 | 3876 | 0.7109          |
| 0.6778        | 1.6670 | 3990 | 0.7102          |
| 0.6772        | 1.7146 | 4104 | 0.7094          |
| 0.682         | 1.7623 | 4218 | 0.7086          |
| 0.681         | 1.8099 | 4332 | 0.7079          |
| 0.6807        | 1.8575 | 4446 | 0.7049          |
| 0.6839        | 1.9052 | 4560 | 0.7048          |
| 0.6821        | 1.9528 | 4674 | 0.7026          |
| 0.6858        | 2.0004 | 4788 | 0.7004          |
| 0.6241        | 2.0480 | 4902 | 0.7086          |
| 0.6297        | 2.0957 | 5016 | 0.7094          |
| 0.6282        | 2.1433 | 5130 | 0.7085          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1