sam2ai
/

gemma_odia_2b

+---
+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

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