peft safetensors gemma axolotl generated_from_trainer base_model:google/gemma-2b license:other 4-bit bitsandbytes region:us
---
license: other
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: google/gemma-2b
model-index:
- name: gemma_odia_2b
  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: google/gemma-2b
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: true
strict: false

# huggingface repo
datasets:
  - path: OdiaGenAIdata/culturax-odia
    type: completion
val_set_size: 0.1
output_dir: ./gemma-odia-2b-pretrain
hub_model_id: sam2ai/gemma_odia_2b

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
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

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 13.3986

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 48.3127       | 0.0   | 1     | 48.2905         |
| 21.4891       | 0.25  | 449   | 21.4957         |
| 25.8116       | 0.5   | 898   | 26.0510         |
| 25.3858       | 0.75  | 1347  | 25.6013         |
| 16.9215       | 1.0   | 1796  | 16.9936         |
| 16.7894       | 1.24  | 2245  | 16.7975         |
| 16.8564       | 1.49  | 2694  | 17.0068         |
| 16.8912       | 1.74  | 3143  | 17.0482         |
| 16.9407       | 1.99  | 3592  | 17.0556         |
| 16.7487       | 2.22  | 4041  | 16.8123         |
| 17.7797       | 2.47  | 4490  | 18.1220         |
| 14.0039       | 2.72  | 4939  | 14.0630         |
| 14.7386       | 2.97  | 5388  | 14.7828         |
| 14.9965       | 3.21  | 5837  | 15.2212         |
| 15.1822       | 3.46  | 6286  | 15.6448         |
| 14.1876       | 3.71  | 6735  | 14.5398         |
| 16.6416       | 3.96  | 7184  | 16.9006         |
| 17.0568       | 4.19  | 7633  | 17.1808         |
| 17.4472       | 4.44  | 8082  | 17.5766         |
| 17.4219       | 4.69  | 8531  | 17.5393         |
| 17.3064       | 4.94  | 8980  | 17.5467         |
| 17.2741       | 5.18  | 9429  | 17.5657         |
| 16.9905       | 5.43  | 9878  | 17.3912         |
| 16.642        | 5.68  | 10327 | 17.1920         |
| 16.6345       | 5.93  | 10776 | 17.1085         |
| 15.5702       | 6.16  | 11225 | 16.0494         |
| 15.3421       | 6.41  | 11674 | 15.9889         |
| 13.1025       | 6.66  | 12123 | 13.1419         |
| 13.1904       | 6.91  | 12572 | 13.2151         |
| 13.261        | 7.15  | 13021 | 13.3119         |
| 13.2333       | 7.4   | 13470 | 13.3195         |
| 13.2705       | 7.65  | 13919 | 13.3380         |
| 13.3417       | 7.9   | 14368 | 13.3804         |
| 13.3553       | 8.13  | 14817 | 13.3902         |
| 13.4078       | 8.38  | 15266 | 13.4614         |
| 13.394        | 8.63  | 15715 | 13.4338         |
| 13.3754       | 8.88  | 16164 | 13.4149         |
| 13.3487       | 9.12  | 16613 | 13.4044         |
| 13.3807       | 9.37  | 17062 | 13.3903         |
| 13.3766       | 9.62  | 17511 | 13.3986         |


### 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