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README.md

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+---
+license: apache-2.0
+base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
+tags:
+- generated_from_trainer
+model-index:
+- name: qlora-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
+adapter: null
+base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
+bf16: auto
+dataset_prepared_path: last_run_prepared
+datasets:
+- path: utrgvseniorproject/medtext
+  type: completion
+debug: null
+deepspeed: null
+early_stopping_patience: null
+evals_per_epoch: null
+flash_attention: false
+fp16: null
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 1
+gradient_checkpointing: true
+group_by_length: false
+is_llama_derived_model: true
+learning_rate: 0.0002
+load_in_4bit: false
+load_in_8bit: false
+local_rank: null
+logging_steps: 1
+lora_alpha: null
+lora_dropout: null
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: null
+lora_target_linear: null
+lora_target_modules: null
+lr_scheduler: cosine
+micro_batch_size: 1
+model_type: LlamaForCausalLM
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+output_dir: ./qlora-out
+pad_to_sequence_len: true
+resume_from_checkpoint: null
+sample_packing: true
+saves_per_epoch: null
+sequence_len: 1096
+special_tokens: null
+strict: false
+tf32: false
+tokenizer_type: LlamaTokenizer
+train_on_inputs: false
+val_set_size: 0.05
+wandb_entity: utrgvmedai
+wandb_log_model: true
+wandb_name: testingTiny
+wandb_project: TinyLlamaLLMTest
+wandb_watch: null
+warmup_steps: 10
+weight_decay: 0.0
+xformers_attention: null
+
+```
+
+</details><br>
+
+# qlora-out
+
+This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+
+## 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: 10
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.0           | 1.02  | 810  | nan             |
+| 0.0           | 1.98  | 1594 | nan             |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.0

checkpoint-1594/config.json

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+{
+  "_name_or_path": "TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
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+  "hidden_act": "silu",
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+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 22,
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+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

checkpoint-1594/generation_config.json

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+  "max_length": 2048,
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+}

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checkpoint-810/config.json

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+  "architectures": [
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+  ],
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+  "transformers_version": "4.38.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

checkpoint-810/generation_config.json

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config.json

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+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "model_type": "llama",
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+}

generation_config.json

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special_tokens_map.json

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tokenizer_config.json

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