|
--- |
|
license: apache-2.0 |
|
base_model: mistralai/Mistral-7B-Instruct-v0.2 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: mistral_fine_out |
|
results: [] |
|
--- |
|
|
|
[<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: `0.3.0` |
|
```yaml |
|
base_model: mistralai/Mistral-7B-Instruct-v0.2 |
|
model_type: MistralForCausalLM |
|
tokenizer_type: LlamaTokenizer |
|
is_mistral_derived_model: true |
|
|
|
load_in_8bit: false |
|
load_in_4bit: false |
|
strict: false |
|
|
|
datasets: |
|
- path: out/train_alpaca.jsonl |
|
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: 4 |
|
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> |
|
|
|
The fine tuning script used for launch was from https://github.com/totallylegitco/healthinsurance-llm w/ run_remote.sh and an INPUT_MODEL=mistral |
|
|
|
|
|
# TotallyLegitCo/fighthealthinsurance_model_v0.3 |
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.2) on the [syntehtic-appeal](https://huggingface.co./datasets/TotallyLegitCo/synthetic-appeals) dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.3954 |
|
|
|
## Model description |
|
|
|
Generate health insurance appeals. Early work. |
|
|
|
## Intended uses & limitations |
|
|
|
Generate health insurance appeals. This is early work and may not be suitable for production. |
|
|
|
## Training and evaluation data |
|
|
|
The syntehtic appeal dataset was used for training and evaluation. Given how the dataset was produced there is likely cross-contamination of the training and eval datasets so loss values are likely understated. |
|
|
|
This model is intended to match the Mistral-7B-Instruct style with ```<s>[INST]Instructions[/INT]``` present (as well as system specific instructions within an extra ```<<SYS><</SYS>```. |
|
|
|
## 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: 4 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 2.0506 | 0.0 | 1 | 2.4510 | |
|
| 0.8601 | 0.2 | 58 | 1.1493 | |
|
| 0.8635 | 0.4 | 116 | 1.1356 | |
|
| 0.869 | 0.61 | 174 | 1.1174 | |
|
| 0.7764 | 0.81 | 232 | 1.1173 | |
|
| 0.7803 | 1.01 | 290 | 1.1124 | |
|
| 0.6902 | 1.2 | 348 | 1.1570 | |
|
| 0.6774 | 1.4 | 406 | 1.1591 | |
|
| 0.6859 | 1.6 | 464 | 1.1651 | |
|
| 0.725 | 1.81 | 522 | 1.1677 | |
|
| 0.6525 | 2.01 | 580 | 1.1686 | |
|
| 0.5069 | 2.2 | 638 | 1.2688 | |
|
| 0.4702 | 2.4 | 696 | 1.2767 | |
|
| 0.4888 | 2.6 | 754 | 1.2852 | |
|
| 0.5197 | 2.8 | 812 | 1.2881 | |
|
| 0.4734 | 3.01 | 870 | 1.2851 | |
|
| 0.3586 | 3.2 | 928 | 1.3856 | |
|
| 0.3889 | 3.4 | 986 | 1.3929 | |
|
| 0.3526 | 3.6 | 1044 | 1.3959 | |
|
| 0.3832 | 3.8 | 1102 | 1.3954 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.0.dev0 |
|
- Pytorch 2.0.1 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|
