|
--- |
|
license: other |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: Qwen/Qwen1.5-MoE-A2.7B |
|
model-index: |
|
- name: 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/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 |
|
base_model: Qwen/Qwen1.5-MoE-A2.7B |
|
trust_remote_code: true |
|
|
|
load_in_8bit: false |
|
load_in_4bit: true |
|
strict: false |
|
|
|
datasets: |
|
- path: mhenrichsen/alpaca_2k_test |
|
type: alpaca |
|
dataset_prepared_path: |
|
val_set_size: 0.05 |
|
output_dir: ./out |
|
|
|
sequence_len: 1024 # supports up to 32k |
|
sample_packing: false |
|
pad_to_sequence_len: false |
|
|
|
adapter: qlora |
|
lora_model_dir: |
|
lora_r: 32 |
|
lora_alpha: 16 |
|
lora_dropout: 0.05 |
|
lora_target_linear: true |
|
lora_fan_in_fan_out: |
|
|
|
wandb_project: |
|
wandb_entity: |
|
wandb_watch: |
|
wandb_name: |
|
wandb_log_model: |
|
|
|
gradient_accumulation_steps: 4 |
|
micro_batch_size: 1 |
|
num_epochs: 4 |
|
optimizer: paged_adamw_8bit |
|
lr_scheduler: cosine |
|
learning_rate: 0.0002 |
|
|
|
train_on_inputs: false |
|
group_by_length: false |
|
bf16: auto |
|
fp16: |
|
tf32: true |
|
|
|
gradient_checkpointing: true |
|
gradient_checkpointing_kwargs: |
|
use_reentrant: false |
|
early_stopping_patience: |
|
resume_from_checkpoint: |
|
local_rank: |
|
logging_steps: 1 |
|
xformers_attention: |
|
flash_attention: true |
|
|
|
warmup_steps: 10 |
|
evals_per_epoch: 4 |
|
saves_per_epoch: 1 |
|
debug: |
|
deepspeed: |
|
weight_decay: 0.0 |
|
fsdp: |
|
fsdp_config: |
|
special_tokens: |
|
|
|
``` |
|
|
|
</details><br> |
|
|
|
# out |
|
|
|
This model is a fine-tuned version of [Qwen/Qwen1.5-MoE-A2.7B](https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.2553 |
|
|
|
## 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 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 4 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 0.8629 | 0.0 | 1 | 0.9370 | |
|
| 0.6917 | 0.25 | 119 | 0.8805 | |
|
| 0.9783 | 0.5 | 238 | 0.8783 | |
|
| 0.9578 | 0.75 | 357 | 0.8827 | |
|
| 0.4772 | 1.0 | 476 | 0.8900 | |
|
| 0.4653 | 1.25 | 595 | 0.9620 | |
|
| 0.5907 | 1.5 | 714 | 0.9532 | |
|
| 0.7364 | 1.75 | 833 | 0.9360 | |
|
| 0.2611 | 2.0 | 952 | 0.9570 | |
|
| 0.1999 | 2.25 | 1071 | 1.0415 | |
|
| 0.1532 | 2.51 | 1190 | 1.0776 | |
|
| 0.0455 | 2.76 | 1309 | 1.0920 | |
|
| 0.087 | 3.01 | 1428 | 1.1094 | |
|
| 0.0183 | 3.26 | 1547 | 1.2266 | |
|
| 0.0135 | 3.51 | 1666 | 1.2604 | |
|
| 0.1929 | 3.76 | 1785 | 1.2553 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.10.0 |
|
- Transformers 4.40.0.dev0 |
|
- Pytorch 2.1.2+cu118 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.0 |
