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---
license: other
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-70B-Instruct
model-index:
- name: empower-functions-llama3-70b-parallel-all-linear
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
adapter: qlora
base_model: meta-llama/Meta-Llama-3-70B-Instruct
bf16: auto
datasets:
- conversation: llama-3
path: a265546be8c24d59bfdc6ba69431b635/./data/with_function_response/original_clean/function_used_training_shuffled.jsonl
type: sharegpt
- conversation: llama-3
path: a265546be8c24d59bfdc6ba69431b635/./data/with_function_response/original_clean/function_not_used_training.jsonl
type: sharegpt
- conversation: llama-3
path: a265546be8c24d59bfdc6ba69431b635/./data/with_function_response/parallel_call/parallel_data_training.jsonl
type: sharegpt
debug: null
deepspeed: null
early_stopping_patience: null
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: null
fsdp:
- full_shard
- auto_wrap
fsdp_config:
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
fsdp_cpu_ram_efficient_loading: true
fsdp_limit_all_gathers: true
fsdp_offload_params: true
fsdp_sharding_strategy: FULL_SHARD
fsdp_state_dict_type: FULL_STATE_DICT
fsdp_sync_module_states: true
fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
fsdp_use_orig_params: false
gradient_accumulation_steps: 2
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
group_by_length: false
hub_model_id: liuylhf/empower-functions-llama3-70b-parallel-all-linear
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules: null
lr_scheduler: cosine
micro_batch_size: 4
model_type: LlamaForCausalLM
num_epochs: 4
optimizer: adamw_torch
output_dir: a265546be8c24d59bfdc6ba69431b635/model
pad_to_sequence_len: true
resume_from_checkpoint: null
sample_packing: true
saves_per_epoch: 10
sequence_len: 4096
special_tokens:
pad_token: <|end_of_text|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0.05
wandb_entity: null
wandb_log_model: null
wandb_name: null
wandb_project: null
wandb_watch: null
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# empower-functions-llama3-70b-parallel-all-linear
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0436
## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.0962 | 0.0067 | 1 | 2.0635 |
| 0.0715 | 0.2492 | 37 | 0.0770 |
| 0.0556 | 0.4983 | 74 | 0.0600 |
| 0.0559 | 0.7475 | 111 | 0.0549 |
| 0.0542 | 0.9966 | 148 | 0.0523 |
| 0.0439 | 1.2256 | 185 | 0.0505 |
| 0.0484 | 1.4747 | 222 | 0.0496 |
| 0.043 | 1.7239 | 259 | 0.0477 |
| 0.0467 | 1.9731 | 296 | 0.0464 |
| 0.0406 | 2.2020 | 333 | 0.0462 |
| 0.0424 | 2.4512 | 370 | 0.0453 |
| 0.0378 | 2.7003 | 407 | 0.0443 |
| 0.0382 | 2.9495 | 444 | 0.0435 |
| 0.0352 | 3.1785 | 481 | 0.0439 |
| 0.0328 | 3.4276 | 518 | 0.0438 |
| 0.0329 | 3.6768 | 555 | 0.0437 |
| 0.0378 | 3.9259 | 592 | 0.0436 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1 |