---
library_name: peft
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 9b0ce33a-0e6b-4448-866c-d786f064ba67
  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: TinyLlama/TinyLlama-1.1B-Chat-v0.6
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 652c37adfdba156e_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/652c37adfdba156e_train_data.json
  type:
    field_instruction: prompt
    field_output: chosen
    format: '{instruction}'
    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/9b0ce33a-0e6b-4448-866c-d786f064ba67
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
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_steps: 500
micro_batch_size: 8
mlflow_experiment_name: /tmp/652c37adfdba156e_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: leixa-personal
wandb_mode: online
wandb_name: f3658745-2da6-44ad-aeb6-c4275a7f6186
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: f3658745-2da6-44ad-aeb6-c4275a7f6186
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 9b0ce33a-0e6b-4448-866c-d786f064ba67

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: 1.3730

## 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: 5e-05
- 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: 288

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0104 | 1    | 1.9109          |
| 1.6823        | 0.25   | 24   | 1.6583          |
| 1.5419        | 0.5    | 48   | 1.5523          |
| 1.5028        | 0.75   | 72   | 1.4936          |
| 1.4711        | 1.0    | 96   | 1.4529          |
| 1.4095        | 1.25   | 120  | 1.4250          |
| 1.4025        | 1.5    | 144  | 1.4069          |
| 1.3641        | 1.75   | 168  | 1.3919          |
| 1.3483        | 2.0    | 192  | 1.3826          |
| 1.3427        | 2.25   | 216  | 1.3779          |
| 1.3168        | 2.5    | 240  | 1.3749          |
| 1.3198        | 2.75   | 264  | 1.3732          |
| 1.3255        | 3.0    | 288  | 1.3730          |


### Framework versions

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