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README.md

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 ---
-license: openrail
+license: other
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: google/gemma-2b-it
+model-index:
+- name: out
+  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-it
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+bnb_config_kwargs:
+  # These are default values
+  llm_int8_has_fp16_weight: false
+  bnb_4bit_quant_type: nf4
+  bnb_4bit_use_double_quant: true
+
+# huggingface repo
+datasets:
+  - path: jayshah5696/samvaad-hi-v1_gemma_format
+    type: completion
+    field: text
+val_set_size: 0.05
+dataset_prepared_path: ./LLM-data
+output_dir: ./out
+
+adapter: qlora
+lora_r: 4
+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_openhathi
+wandb_run_id: model_03_qlora
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+
+gradient_accumulation_steps: 2
+micro_batch_size: 2
+num_epochs: 1
+optimizer: paged_adamw_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+
+train_on_inputs: false
+group_by_length: false
+bf16: false
+fp16: false
+tf32: false
+
+bfloat16: true
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 10
+xformers_attention:
+flash_attention: true
+
+warmup_ratio: 0.05
+evals_per_epoch: 5
+eval_table_size:
+# eval_max_new_tokens: 128
+metric_for_best_model: "eval_loss"
+saves_per_epoch: 20
+save_total_limit: 20 
+load_best_model_at_end: True
+
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+
+seed: 108
+
+```
+
+</details><br>
+
+# out
+
+This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5293
+
+## 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: 108
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 453
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| No log        | 0.0   | 1    | 3.7785          |
+| 1.6305        | 0.2   | 965  | 1.6443          |
+| 1.5355        | 0.4   | 1930 | 1.5893          |
+| 1.5383        | 0.6   | 2895 | 1.5557          |
+| 1.5223        | 0.8   | 3860 | 1.5350          |
+| 1.5477        | 1.0   | 4825 | 1.5293          |
+
+
+### Framework versions
+
+- PEFT 0.8.2
+- Transformers 4.39.0.dev0
+- Pytorch 2.2.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.0

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