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Model: TotallyLegitCo/fighthealthinsurance_model_v0.5
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+tags:
+- generated_from_trainer
+model-index:
+- name: mistral_fine_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/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: `0.4.1`
+```yaml
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+is_mistral_derived_model: true
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - data_files: out/train.jsonl
+    path: out/
+    ds_type: json
+    type:
+      alpaca
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./mistral_fine_out
+
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_run_id:
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.000005
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+auto_resume_from_checkpoint: true
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 10
+eval_steps: 0.05
+eval_table_size:
+eval_table_max_new_tokens: 128
+save_steps:
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
+model_config:
+  sliding_window: 4096
+
+```
+
+</details><br>
+
+# mistral_fine_out
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on a synthetic appeals dataset.
+See the [health insurance fine tuning repo](https://github.com/totallylegitco/healthinsurance-llm) for details.
+An earlier [version of this dataset is availabile](https://huggingface.co/datasets/TotallyLegitCo/synthetic-appeals).
+
+It achieves the following results on the evaluation set:
+- Loss: 0.7984
+
+## Model description
+
+Generate health insurance appeals. Early work.
+
+
+## Intended uses & limitations
+
+
+It is intended to be used as part of the [fight health insurance web app](https://www.fighthealthinsurance.com/) [who's repo is at https://github.com/totallylegitco/fighthealthinsurance](https://github.com/totallylegitco/fighthealthinsurance)
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- 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 |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.0397        | 0.0004 | 1    | 1.1590          |
+| 0.6084        | 0.1002 | 230  | 0.7272          |
+| 0.5195        | 0.2003 | 460  | 0.7141          |
+| 0.4713        | 0.3005 | 690  | 0.7090          |
+| 0.3973        | 0.4007 | 920  | 0.7097          |
+| 0.3306        | 0.5009 | 1150 | 0.7145          |
+| 0.3507        | 0.6010 | 1380 | 0.7136          |
+| 0.3125        | 0.7012 | 1610 | 0.7200          |
+| 0.3055        | 0.8014 | 1840 | 0.7227          |
+| 0.2027        | 0.9016 | 2070 | 0.7301          |
+| 0.2632        | 1.0017 | 2300 | 0.7471          |
+| 0.2077        | 1.0851 | 2530 | 0.7662          |
+| 0.0992        | 1.1853 | 2760 | 0.7744          |
+| 0.236         | 1.2855 | 2990 | 0.7844          |
+| 0.1572        | 1.3857 | 3220 | 0.7915          |
+| 0.192         | 1.4858 | 3450 | 0.7921          |
+| 0.1812        | 1.5860 | 3680 | 0.7968          |
+| 0.1973        | 1.6862 | 3910 | 0.7979          |
+| 0.1422        | 1.7864 | 4140 | 0.7982          |
+| 0.1315        | 1.8865 | 4370 | 0.7984          |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.42.3",
+  "use_cache": false,
+  "vocab_size": 32768
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.42.3"
+}

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