---
license: apache-2.0
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
model-index:
- name: alpaca-cleaned-tiny-llama
  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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer

load_in_8bit: true
load_in_4bit: false
strict: false

datasets:
  # - path: mhenrichsen/alpaca_2k_test
  - path: yahma/alpaca-cleaned
    type: alpaca
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/alpaca-cleaned-tiny-llama
hub_model_id: ahmedsamirio/alpaca-cleaned-tiny-llama

sequence_len: 4096
sample_packing: true
eval_sample_packing: true
pad_to_sequence_len: true

adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: alpaca-tiny-llama
wandb_entity: ahmedsamirio
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:

```

</details><br>

# alpaca-cleaned-tiny-llama

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1115

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3435        | 0.0029 | 1    | 1.4128          |
| 1.1926        | 0.2498 | 85   | 1.1723          |
| 1.1275        | 0.4996 | 170  | 1.1518          |
| 1.1153        | 0.7494 | 255  | 1.1410          |
| 1.1289        | 0.9993 | 340  | 1.1312          |
| 1.1267        | 1.2278 | 425  | 1.1276          |
| 1.1053        | 1.4776 | 510  | 1.1220          |
| 1.1261        | 1.7274 | 595  | 1.1172          |
| 1.0991        | 1.9772 | 680  | 1.1144          |
| 1.0295        | 2.2057 | 765  | 1.1157          |
| 1.086         | 2.4555 | 850  | 1.1131          |
| 1.029         | 2.7054 | 935  | 1.1114          |
| 1.019         | 2.9552 | 1020 | 1.1108          |
| 1.0158        | 3.1830 | 1105 | 1.1113          |
| 1.0297        | 3.4328 | 1190 | 1.1123          |
| 1.0571        | 3.6826 | 1275 | 1.1116          |
| 1.0306        | 3.9324 | 1360 | 1.1115          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1