|
--- |
|
license: apache-2.0 |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: mistralai/Mistral-7B-v0.1 |
|
model-index: |
|
- name: med_Mistral |
|
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: qlora |
|
base_model: mistralai/Mistral-7B-v0.1 |
|
bf16: false |
|
dataset_prepared_path: null |
|
datasets: |
|
- path: joseagmz/MedQnA_version3 |
|
type: context_qa.load_v2 |
|
debug: null |
|
deepspeed: null |
|
early_stopping_patience: null |
|
evals_per_epoch: null |
|
flash_attention: false |
|
fp16: true |
|
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: true |
|
load_in_8bit: false |
|
local_rank: null |
|
logging_steps: 1 |
|
lora_alpha: 16 |
|
lora_dropout: 0.05 |
|
lora_fan_in_fan_out: null |
|
lora_model_dir: null |
|
lora_r: 32 |
|
lora_target_linear: true |
|
lora_target_modules: null |
|
lr_scheduler: cosine |
|
max_steps: 20 |
|
micro_batch_size: 1 |
|
mlflow_experiment_name: colab-example |
|
model_type: MistralForCausalLM |
|
num_epochs: 4 |
|
optimizer: paged_adamw_32bit |
|
output_dir: ./med_Mistral |
|
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: null |
|
wandb_log_model: null |
|
wandb_name: null |
|
wandb_project: null |
|
wandb_watch: null |
|
warmup_steps: 10 |
|
weight_decay: 0.0 |
|
xformers_attention: null |
|
|
|
``` |
|
|
|
</details><br> |
|
|
|
# med_Mistral |
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.3152 |
|
|
|
## 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 |
|
- training_steps: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.9831 | 0.0 | 20 | 1.3152 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.8.2 |
|
- Transformers 4.38.0.dev0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.0 |
