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README.md

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+---
+license: mit
+base_model: microsoft/Phi-3-mini-4k-instruct
+tags:
+- generated_from_trainer
+model-index:
+- name: phi3-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: `0.4.1`
+```yaml
+base_model: microsoft/Phi-3-mini-4k-instruct
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+trust_remote_code: true
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: dataset.json
+    ds_type: json
+    type: completion
+
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./phi3-out
+
+sequence_len: 4096
+sample_packing: false
+#pad_to_sequence_len: true
+
+adapter:
+lora_model_dir:
+lora_r:
+lora_alpha:
+lora_dropout:
+lora_target_linear:
+lora_fan_in_fan_out:
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 1
+micro_batch_size: 1
+num_epochs: 2
+optimizer: adamw_torch
+# adam_beta2: 0.95
+# adam_epsilon: 0.00001
+# max_grad_norm: 1.0
+lr_scheduler: cosine
+learning_rate: 0.0002 # 0.000003 #0.0002
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: true
+
+# gradient_checkpointing: true
+# gradient_checkpointing_kwargs:
+#   use_reentrant: True
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+#warmup_steps: 100
+#evals_per_epoch: 4
+# saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+#resize_token_embeddings_to_32x: true
+special_tokens:
+  pad_token: "<|endoftext|>"
+  eos_token: "<|end|>"
+```
+
+</details><br>
+
+# phi3-out
+
+This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8809
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 0.4023        | 1.0   | 7628  | 1.4132          |
+| 0.1342        | 2.0   | 15256 | 1.8809          |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1