|
--- |
|
base_model: mistralai/Mistral-Small-Instruct-2409 |
|
library_name: peft |
|
license: other |
|
tags: |
|
- axolotl |
|
- generated_from_trainer |
|
model-index: |
|
- name: mistral-small-adventure-qlora |
|
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 |
|
# huggingface-cli login --token $hf_key && wandb login $wandb_key |
|
# python -m axolotl.cli.preprocess ms-adventure.yml |
|
# accelerate launch -m axolotl.cli.train ms-adventure.yml |
|
# python -m axolotl.cli.merge_lora ms-adventure.yml |
|
|
|
base_model: mistralai/Mistral-Small-Instruct-2409 |
|
model_type: AutoModelForCausalLM |
|
tokenizer_type: AutoTokenizer |
|
|
|
load_in_8bit: false |
|
load_in_4bit: true |
|
strict: false |
|
sequence_len: 16384 # 99% vram |
|
min_sample_len: 128 |
|
bf16: true |
|
fp16: |
|
tf32: false |
|
flash_attention: true |
|
special_tokens: |
|
|
|
# Data |
|
dataset_prepared_path: last_run_prepared |
|
datasets: |
|
- path: ColumbidAI/adventure-ms-16k |
|
type: completion |
|
warmup_steps: 20 |
|
shuffle_merged_datasets: true |
|
|
|
save_safetensors: true |
|
|
|
# WandB |
|
wandb_project: Mistral-Small-Skein |
|
wandb_entity: |
|
|
|
# Iterations |
|
num_epochs: 1 |
|
|
|
# Output |
|
output_dir: ./adventure-workspace |
|
hub_model_id: ToastyPigeon/mistral-small-adventure-qlora |
|
hub_strategy: "all_checkpoints" |
|
saves_per_epoch: 5 |
|
|
|
# Sampling |
|
sample_packing: true |
|
pad_to_sequence_len: true |
|
|
|
# Batching |
|
gradient_accumulation_steps: 4 |
|
micro_batch_size: 1 |
|
eval_batch_size: 1 |
|
gradient_checkpointing: 'unsloth' |
|
gradient_checkpointing_kwargs: |
|
use_reentrant: true |
|
|
|
#unsloth_cross_entropy_loss: true |
|
#unsloth_lora_mlp: true |
|
#unsloth_lora_qkv: true |
|
#unsloth_lora_o: true |
|
|
|
# Evaluation |
|
val_set_size: 100 |
|
evals_per_epoch: 5 |
|
eval_table_size: |
|
eval_max_new_tokens: 256 |
|
eval_sample_packing: false |
|
|
|
# LoRA |
|
adapter: qlora |
|
lora_model_dir: |
|
lora_r: 64 |
|
lora_alpha: 32 |
|
lora_dropout: 0.125 |
|
lora_target_linear: |
|
lora_fan_in_fan_out: |
|
lora_target_modules: |
|
- gate_proj |
|
- down_proj |
|
- up_proj |
|
- q_proj |
|
- v_proj |
|
- k_proj |
|
- o_proj |
|
lora_modules_to_save: |
|
|
|
# Optimizer |
|
optimizer: paged_adamw_8bit # adamw_8bit |
|
lr_scheduler: cosine |
|
learning_rate: 0.0001 |
|
cosine_min_lr_ratio: 0.1 |
|
weight_decay: 0.01 |
|
max_grad_norm: 10.0 |
|
|
|
# Misc |
|
train_on_inputs: false |
|
group_by_length: false |
|
early_stopping_patience: |
|
local_rank: |
|
logging_steps: 1 |
|
xformers_attention: |
|
debug: |
|
deepspeed: /workspace/axolotl/deepspeed_configs/zero3.json # previously blank |
|
fsdp: |
|
fsdp_config: |
|
|
|
# Checkpoints |
|
resume_from_checkpoint: |
|
|
|
|
|
plugins: |
|
- axolotl.integrations.liger.LigerPlugin |
|
liger_rope: true |
|
liger_rms_norm: true |
|
liger_swiglu: true |
|
liger_fused_linear_cross_entropy: true |
|
``` |
|
|
|
</details><br> |
|
|
|
# mistral-small-adventure-qlora |
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-Small-Instruct-2409](https://huggingface.co/mistralai/Mistral-Small-Instruct-2409) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.9117 |
|
|
|
## 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: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 2 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 8 |
|
- total_eval_batch_size: 2 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 20 |
|
- num_epochs: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 1.8182 | 0.0035 | 1 | 2.1284 | |
|
| 1.8279 | 0.2043 | 59 | 1.9991 | |
|
| 1.8002 | 0.4087 | 118 | 1.9488 | |
|
| 1.7188 | 0.6130 | 177 | 1.9185 | |
|
| 1.7306 | 0.8173 | 236 | 1.9117 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.13.0 |
|
- Transformers 4.45.0 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.20.0 |
