mimic3-mistral-7B-v0.1

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<details><summary>See axolotl config</summary>

axolotl version: 0.4.0

base_model: mistralai/Mistral-7B-v0.1
hub_model_id: chaosIsRythmic/mimic3-mistral-7B-v0.1

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  # This will be the path used for the data when it is saved to the Volume in the cloud.
  - path: data.jsonl
    ds_type: json
    type:
      # JSONL file contains question, context, answer fields per line.
      # This gets mapped to instruction, input, output axolotl tags.
      field_instruction: question
      field_input: context
      field_output: answer
      # Format is used by axolotl to generate the prompt.
      format: |-
        [INST] Using the medical notes below, assign the right ICD-9 codes.
        {input}
        {instruction} [/INST]

tokens: # add new control tokens from the dataset to the model
  - "[INST]"
  - " [/INST]"
  - "[SQL]"
  - " [/SQL]"

dataset_prepared_path: last_run_prepared
val_set_size: 0.2
output_dir: ./lora-out

sequence_len: 4096
sample_packing: false
eval_sample_packing: false
pad_to_sequence_len: false
pad_to_sequence_len: true

adapter: lora
lora_model_dir:
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_modules_to_save: # required when adding new tokens to LLaMA/Mistral
  - embed_tokens
  - lm_head

wandb_project:  mimic3
wandb_entity:
wandb_watch:
wandb_run_id:

loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3

gradient_accumulation_steps: 1
micro_batch_size: 6
num_epochs: 6
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0001

bf16: auto
fp16: false
tf32: false
train_on_inputs: false
group_by_length: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
saves_per_epoch: 1
evals_per_epoch: 4
eval_max_new_tokens: 128
debug:
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"

</details><br>

mimic3-mistral-7B-v0.1

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6757

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: 0.0001
• train_batch_size: 6
• eval_batch_size: 6
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• total_train_batch_size: 12
• total_eval_batch_size: 12
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 10
• num_epochs: 6

Training results

Framework versions

• PEFT 0.10.0
• Transformers 4.40.2
• Pytorch 2.2.2+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1