|
--- |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: openaccess-ai-collective/tiny-mistral |
|
model-index: |
|
- name: axolotl-test |
|
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) |
|
## axolotl config |
|
axolotl version: `0.3.0` |
|
```yaml |
|
base_model: openaccess-ai-collective/tiny-mistral |
|
flash_attention: true |
|
sequence_len: 1024 |
|
load_in_8bit: true |
|
adapter: lora |
|
lora_r: 32 |
|
lora_alpha: 64 |
|
lora_dropout: 0.05 |
|
lora_target_linear: true |
|
val_set_size: 0.1 |
|
special_tokens: |
|
unk_token: <unk> |
|
bos_token: <s> |
|
eos_token: </s> |
|
datasets: |
|
- path: mhenrichsen/alpaca_2k_test |
|
type: alpaca |
|
num_epochs: 2 |
|
micro_batch_size: 2 |
|
gradient_accumulation_steps: 1 |
|
output_dir: temp_dir |
|
learning_rate: 0.00001 |
|
optimizer: adamw_torch |
|
lr_scheduler: cosine |
|
max_steps: 20 |
|
save_steps: 10 |
|
eval_steps: 10 |
|
hub_model_id: hamel/axolotl-test |
|
dataset_processes: 1 |
|
``` |
|
# axolotl-test |
|
|
|
This model is a fine-tuned version of [openaccess-ai-collective/tiny-mistral](https://huggingface.co/openaccess-ai-collective/tiny-mistral) on the None dataset. |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- training_steps: 20 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.0.dev0 |
|
- Pytorch 2.1.0 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
## Training procedure |
|
|
|
|
|
The following `bitsandbytes` quantization config was used during training: |
|
- quant_method: bitsandbytes |
|
- load_in_8bit: True |
|
- load_in_4bit: None |
|
- llm_int8_threshold: 6.0 |
|
- llm_int8_skip_modules: None |
|
- llm_int8_enable_fp32_cpu_offload: False |
|
- llm_int8_has_fp16_weight: False |
|
- bnb_4bit_quant_type: fp4 |
|
- bnb_4bit_use_double_quant: False |
|
- bnb_4bit_compute_dtype: float32 |
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.6.0 |
|
|
