Upload README.md

README.md

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+---
+library_name: peft
+license: mit
+base_model: microsoft/phi-1_5
+tags:
+- generated_from_trainer
+datasets:
+- bitext/Bitext-retail-banking-llm-chatbot-training-dataset
+model-index:
+- name: workspace/outputs/phi-bankingqa-out5
+  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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.10.0.dev0`
+```yaml
+base_model: microsoft/phi-1_5
+# optionally might have model_type or tokenizer_type
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+# Automatically upload checkpoint and final model to HF
+# hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: true
+
+datasets:
+  - #path: garage-bAInd/Open-Platypus
+    path: /workspace/data/alpaca_corrected_bankingqa.jsonl
+    type: alpaca
+
+dataset_prepared_path:
+val_set_size: 0.1
+output_dir: /workspace/outputs/phi-bankingqa-out5
+
+
+sequence_len: 1024 #reduced to hasten training
+sample_packing: true
+pad_to_sequence_len: true
+
+#axolotl own suggestion
+eval_sample_packing: False
+
+adapter: qlora
+#lora_model_dir:
+lora_r: 16
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_linear: true
+
+wandb_project: phi1.5-bankingqa-finetune
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 8 #increase to hasten training
+micro_batch_size: 4
+gradient_checkpointing: true #added to hasten training
+num_epochs: 1
+optimizer: adamw_torch_fused
+adam_beta2: 0.95
+adam_epsilon: 0.00001
+max_grad_norm: 1.0
+lr_scheduler: cosine
+weight_decay: 0.01 # added to hasten training
+learning_rate: 0.0002
+
+bf16: auto
+#tf32: true
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: True
+resume_from_checkpoint:
+logging_steps: 1
+#flash_attention: true
+flash_attention: false
+
+warmup_steps: 100
+evals_per_epoch: 4
+saves_per_epoch: 1
+weight_decay: 0.1
+resize_token_embeddings_to_32x: true
+special_tokens:
+  pad_token: "<|endoftext|>"
+```
+
+</details><br>
+
+# workspace/outputs/phi-bankingqa-out5
+
+This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the /workspace/data/alpaca_corrected_bankingqa.jsonl dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1071
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-05 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.8635        | 0.0208 | 1    | 1.2920          |
+| 2.8745        | 0.2494 | 12   | 1.2862          |
+| 2.7446        | 0.4987 | 24   | 1.2616          |
+| 2.4361        | 0.7481 | 36   | 1.1899          |
+| 2.0611        | 0.9974 | 48   | 1.1071          |
+
+
+### Framework versions
+
+- PEFT 0.15.2
+- Transformers 4.51.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1