---
license: apache-2.0
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: unsloth/gemma-2b
model-index:
- name: gemma_odia_2b_unsloth
  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: `0.4.0`
```yaml
# use google/gemma-7b if you have access
base_model: unsloth/gemma-2b
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: true
strict: false

# huggingface repo
datasets:
  - path: OdiaGenAIdata/culturax-gemma-data
    type: completion
val_set_size: 0.1
output_dir: ./gemma-odia-2b-pretrain-unsloth
hub_model_id: sam2ai/gemma_odia_2b_unsloth

adapter: qlora
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

wandb_project: gemma-completion-2b-odia-unsloth
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:


gradient_accumulation_steps: 3
micro_batch_size: 2
num_epochs: 10
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: false

warmup_ratio: 0.1
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:

```

</details><br>

# gemma_odia_2b_unsloth

This model is a fine-tuned version of [unsloth/gemma-2b](https://huggingface.co/unsloth/gemma-2b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4007

## 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
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 3
- total_train_batch_size: 48
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 87
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 48.3499       | 0.0   | 1     | 48.2901         |
| 22.3743       | 0.25  | 449   | 22.4176         |
| 22.3342       | 0.5   | 898   | 22.3606         |
| 9.2934        | 0.75  | 1347  | 9.2611          |
| 3.8237        | 1.0   | 1796  | 3.5233          |
| 4.7071        | 1.24  | 2245  | 4.3919          |
| 5.0601        | 1.49  | 2694  | 4.8608          |
| 3.966         | 1.74  | 3143  | 3.7664          |
| 3.7972        | 1.99  | 3592  | 3.6383          |
| 3.802         | 2.22  | 4041  | 3.4831          |
| 3.7412        | 2.47  | 4490  | 3.4955          |
| 3.6174        | 2.72  | 4939  | 3.4462          |
| 3.6126        | 2.97  | 5388  | 3.3908          |
| 3.5759        | 3.2   | 5837  | 3.3827          |
| 3.4854        | 3.45  | 6286  | 3.3748          |
| 3.4987        | 3.7   | 6735  | 3.2868          |
| 14.4221       | 3.95  | 7184  | 14.0660         |
| 16.2072       | 4.19  | 7633  | 15.8277         |
| 3.5762        | 4.44  | 8082  | 3.3616          |
| 15.155        | 4.69  | 8531  | 15.1050         |
| 3.7657        | 4.94  | 8980  | 3.6526          |
| 5.0469        | 5.17  | 9429  | 4.8438          |
| 4.0484        | 5.42  | 9878  | 3.8946          |
| 4.0601        | 5.67  | 10327 | 3.8040          |
| 3.7711        | 5.92  | 10776 | 3.5799          |
| 3.6364        | 6.16  | 11225 | 3.4930          |
| 3.5855        | 6.41  | 11674 | 3.4586          |
| 3.5484        | 6.66  | 12123 | 3.4197          |
| 3.8341        | 6.91  | 12572 | 3.6314          |
| 3.5392        | 7.14  | 13021 | 3.4121          |
| 3.6463        | 7.39  | 13470 | 3.3959          |
| 3.6237        | 7.64  | 13919 | 3.4071          |
| 3.542         | 7.89  | 14368 | 3.4076          |
| 3.5737        | 8.13  | 14817 | 3.4041          |
| 3.6167        | 8.38  | 15266 | 3.4153          |
| 3.6356        | 8.63  | 15715 | 3.4068          |
| 3.5233        | 8.88  | 16164 | 3.4054          |
| 3.5382        | 9.11  | 16613 | 3.4019          |
| 3.5788        | 9.36  | 17062 | 3.4008          |
| 3.7003        | 9.61  | 17511 | 3.4007          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.40.0.dev0
- Pytorch 2.4.0.dev20240326+rocm6.0
- Datasets 2.18.0
- Tokenizers 0.15.0