Brian Tang
Adds axolotl config, lora usage notebook
f65013c
---
base_model: openlm-research/open_llama_3b_v2
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: outputs/lora-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/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: openlm-research/open_llama_3b_v2
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: true
load_in_4bit: false
strict: false
push_dataset_to_hub:
datasets:
- path: teknium/GPT4-LLM-Cleaned
type: alpaca
dataset_prepared_path: ./last_run_prepared
val_set_size: 0.02
adapter: lora
lora_model_dir:
sequence_len: 1024
sample_packing: true
lora_r: 8
lora_alpha: 16
lora_dropout: 0.0
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
lora_fan_in_fan_out:
wandb_project: openllama-axolotl
wandb_entity: ashrielbrian
wandb_watch:
wandb_name:
wandb_log_model:
output_dir: ./outputs/lora-out
gradient_accumulation_steps: 1
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
torchdistx_path:
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: false
fp16: true
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint: ./outputs/lora-out/checkpoint-10762
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
gptq_groupsize:
s2_attention:
gptq_model_v1:
warmup_steps: 20
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"
```
</details><br>
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ashrielbrian/openllama-axolotl/runs/y4gkw5cu)
# outputs/lora-out
This model is a fine-tuned version of [openlm-research/open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0423
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.4066 | 0.0002 | 1 | 1.6832 |
| 0.9583 | 0.2501 | 1346 | 1.1052 |
| 1.0801 | 0.5003 | 2692 | 1.0731 |
| 0.8311 | 0.7504 | 4038 | 1.0377 |
| 0.9795 | 1.0006 | 5384 | 1.0241 |
| 0.9849 | 1.2334 | 6730 | 1.0143 |
| 1.1134 | 1.4836 | 8076 | 1.0098 |
| 0.916 | 1.7337 | 9422 | 1.0073 |
| 0.8791 | 2.0011 | 10768 | 1.0076 |
| 1.1143 | 2.2513 | 12114 | 1.0257 |
| 1.1426 | 2.5014 | 13460 | 1.0169 |
| 1.0163 | 2.7515 | 14806 | 1.0169 |
| 0.8814 | 3.0017 | 16152 | 1.0085 |
| 0.8806 | 3.2338 | 17498 | 1.0438 |
| 0.9132 | 3.4839 | 18844 | 1.0442 |
| 0.7981 | 3.7341 | 20190 | 1.0423 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1