---
library_name: peft
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6
tags:
- axolotl
- generated_from_trainer
model-index:
- name: e044dcfc-83e2-4fa2-aad2-875a52316c8d
  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_resume_from_checkpoints: true
base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6
bf16: auto
chat_template: llama3
dataset_prepared_path: null
dataset_processes: 6
datasets:
- data_files:
  - a9d4324f1e33f9ae_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/a9d4324f1e33f9ae_train_data.json
  type:
    field_instruction: init_prompt
    field_output: init_response
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 200
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
hub_model_id: error577/e044dcfc-83e2-4fa2-aad2-875a52316c8d
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: null
micro_batch_size: 16
mlflow_experiment_name: /tmp/a9d4324f1e33f9ae_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
save_steps: 200
sequence_len: 256
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: 2a9710ae-957a-477d-91f9-0a8bce2d110f
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 2a9710ae-957a-477d-91f9-0a8bce2d110f
warmup_steps: 30
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# e044dcfc-83e2-4fa2-aad2-875a52316c8d

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v0.6](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v0.6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2170

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 30
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.2866        | 0.0007 | 1    | 1.2665          |
| 0.7368        | 0.1473 | 200  | 0.7152          |
| 0.6216        | 0.2947 | 400  | 0.6414          |
| 0.5531        | 0.4420 | 600  | 0.5916          |
| 0.4998        | 0.5893 | 800  | 0.5468          |
| 0.4112        | 0.7366 | 1000 | 0.5108          |
| 0.4076        | 0.8840 | 1200 | 0.4649          |
| 0.2988        | 1.0313 | 1400 | 0.4229          |
| 0.3479        | 1.1786 | 1600 | 0.3908          |
| 0.3133        | 1.3260 | 1800 | 0.3472          |
| 0.2523        | 1.4733 | 2000 | 0.3261          |
| 0.2227        | 1.6206 | 2200 | 0.2928          |
| 0.2482        | 1.7680 | 2400 | 0.2750          |
| 0.2354        | 1.9153 | 2600 | 0.2585          |
| 0.1221        | 2.0626 | 2800 | 0.2463          |
| 0.1213        | 2.2099 | 3000 | 0.2326          |
| 0.132         | 2.3573 | 3200 | 0.2288          |
| 0.1477        | 2.5046 | 3400 | 0.2223          |
| 0.1168        | 2.6519 | 3600 | 0.2196          |
| 0.1501        | 2.7993 | 3800 | 0.2174          |
| 0.1196        | 2.9466 | 4000 | 0.2170          |


### Framework versions

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