|
--- |
|
base_model: mistralai/Mistral-Nemo-Base-2407 |
|
library_name: peft |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: qlora_outputs |
|
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 |
|
base_model: mistralai/Mistral-Nemo-Base-2407 |
|
model_type: AutoModelForCausalLM |
|
tokenizer_type: AutoTokenizer |
|
|
|
load_in_8bit: false |
|
load_in_4bit: true |
|
strict: false |
|
|
|
plugins: |
|
- axolotl.integrations.liger.LigerPlugin |
|
liger_rope: true |
|
liger_rms_norm: true |
|
liger_swiglu: true |
|
liger_fused_linear_cross_entropy: true |
|
|
|
adapter: qlora |
|
lora_r: 32 |
|
lora_alpha: 16 |
|
lora_dropout: 0.05 |
|
lora_target_linear: true |
|
lora_fan_in_fan_out: |
|
|
|
datasets: |
|
- path: /home/austin/disk1/summaries_fixed.jsonl |
|
type: sharegpt |
|
dataset_prepared_path: last_run_prepared |
|
val_set_size: 0.01 |
|
output_dir: ./qlora_outputs |
|
|
|
sequence_len: 8192 |
|
sample_packing: true |
|
eval_sample_packing: false |
|
pad_to_sequence_len: true |
|
|
|
wandb_project: summarization-qlora |
|
wandb_entity: |
|
wandb_watch: |
|
wandb_name: actual_run1 |
|
wandb_log_model: |
|
|
|
#unsloth_cross_entropy_loss: true |
|
|
|
gradient_accumulation_steps: 1 |
|
micro_batch_size: 1 |
|
num_epochs: 4 |
|
optimizer: adamw_bnb_8bit |
|
lr_scheduler: cosine |
|
learning_rate: 0.0002 |
|
|
|
train_on_inputs: false |
|
group_by_length: false |
|
bf16: auto |
|
fp16: |
|
tf32: false |
|
|
|
gradient_checkpointing: true |
|
gradient_checkpointing_kwargs: |
|
use_reentrant: false |
|
early_stopping_patience: |
|
resume_from_checkpoint: |
|
logging_steps: 1 |
|
xformers_attention: false |
|
flash_attention: true |
|
|
|
loss_watchdog_threshold: 5.0 |
|
loss_watchdog_patience: 3 |
|
|
|
warmup_steps: 25 |
|
evals_per_epoch: 4 |
|
eval_table_size: |
|
saves_per_epoch: 4 |
|
debug: |
|
deepspeed: ./deepspeed_configs/zero2.json |
|
weight_decay: 0.0 |
|
fsdp: |
|
# - full_shard |
|
# - auto_wrap |
|
fsdp_config: |
|
# fsdp_limit_all_gathers: true |
|
# fsdp_activation_checkpointing: true |
|
# fsdp_sync_module_states: true |
|
# fsdp_offload_params: false |
|
# fsdp_use_orig_params: false |
|
# fsdp_cpu_ram_efficient_loading: false |
|
# fsdp_transformer_layer_cls_to_wrap: MistralDecoderLayer |
|
# fsdp_state_dict_type: FULL_STATE_DICT |
|
# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP |
|
special_tokens: |
|
pad_token: </s> |
|
|
|
``` |
|
|
|
</details><br> |
|
|
|
# qlora_outputs |
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5617 |
|
|
|
## 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 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- total_train_batch_size: 4 |
|
- total_eval_batch_size: 4 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 25 |
|
- num_epochs: 4 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 2.0177 | 0.0014 | 1 | 1.6514 | |
|
| 1.6259 | 0.2507 | 177 | 1.2032 | |
|
| 1.4232 | 0.5014 | 354 | 1.1897 | |
|
| 1.6835 | 0.7521 | 531 | 1.1985 | |
|
| 1.6514 | 1.0028 | 708 | 1.1874 | |
|
| 1.4538 | 1.2365 | 885 | 1.2166 | |
|
| 1.2421 | 1.4873 | 1062 | 1.2224 | |
|
| 1.2844 | 1.7380 | 1239 | 1.2330 | |
|
| 1.4152 | 1.9887 | 1416 | 1.2345 | |
|
| 1.1668 | 2.2252 | 1593 | 1.3476 | |
|
| 1.1249 | 2.4759 | 1770 | 1.3608 | |
|
| 0.921 | 2.7266 | 1947 | 1.3793 | |
|
| 0.7824 | 2.9773 | 2124 | 1.3906 | |
|
| 1.1759 | 3.2040 | 2301 | 1.5438 | |
|
| 0.6625 | 3.4547 | 2478 | 1.5644 | |
|
| 0.8959 | 3.7054 | 2655 | 1.5617 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.44.0 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
