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isafpr-llama3-lora
strickvl/isafpr-llama3-lora
isafpr-llama3-lora is a machine learning model from strickvl. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as llama3.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- llama3
- Model type
- llama
- Access
- Public
- Created
- Jun 13, 2024
- Updated
- Jun 13, 2024
- SHA
- 89297e56
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
<details><summary>See axolotl config</summary>
axolotl version: 0.4.1
base_model: meta-llama/Meta-Llama-3-8B
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
data_seed: 42
seed: 42
datasets:
- path: data/isaf_press_releases_ft.jsonl
conversation: alpaca
type: sharegpt
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/llama3/lora-out
hub_model_id: strickvl/isafpr-llama3-lora
sequence_len: 2048
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_modules_to_save:
- embed_tokens
- lm_head
wandb_project: isaf_pr_ft
wandb_entity: strickvl
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
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
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
s2_attention:
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
pad_token: <|end_of_text|>
isafpr-llama3-lora
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0371
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
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 10
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0023 | 0.0173 | 1 | 2.0120 |
| 0.0975 | 0.2597 | 15 | 0.0792 |
| 0.0576 | 0.5195 | 30 | 0.0586 |
| 0.0317 | 0.7792 | 45 | 0.0476 |
| 0.0367 | 1.0390 | 60 | 0.0445 |
| 0.0315 | 1.2078 | 75 | 0.0421 |
| 0.0249 | 1.4675 | 90 | 0.0429 |
| 0.0302 | 1.7273 | 105 | 0.0380 |
| 0.0264 | 1.9870 | 120 | 0.0376 |
| 0.0184 | 2.1515 | 135 | 0.0362 |
| 0.0174 | 2.4113 | 150 | 0.0366 |
| 0.0152 | 2.6710 | 165 | 0.0373 |
| 0.016 | 2.9307 | 180 | 0.0361 |
| 0.0128 | 3.0996 | 195 | 0.0361 |
| 0.0172 | 3.3593 | 210 | 0.0369 |
| 0.0086 | 3.6190 | 225 | 0.0371 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- Type
- llama
- License
- llama3
- Created
- Jun 13, 2024
- Updated
- Jun 13, 2024