Downloads · 30 days
4
20% of all-time downloads
db4fa482-19bd-4cd7-a722-d106a826e3e5
infogep/db4fa482-19bd-4cd7-a722-d106a826e3e5
db4fa482-19bd-4cd7-a722-d106a826e3e5 is a machine learning model from infogep. 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 llama3.1.
should probably proofread and complete it, then remove this comment. --
All-time downloads
20
Public
Repo size
185 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin84.1 MB · 45%
At a glance
- Library
- peft
- License
- llama3.1
- Model type
- llama
- Access
- Public
- Created
- Jan 24, 2025
- Updated
- Jan 24, 2025
- SHA
- fc91fa05
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
adapter: lora
base_model: unsloth/Meta-Llama-3.1-8B-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- c9e5168aaf615a7c_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/c9e5168aaf615a7c_train_data.json
type:
field_instruction: problem
field_output: target_answer
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 5
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: true
hub_model_id: infogep/db4fa482-19bd-4cd7-a722-d106a826e3e5
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 3
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_steps: 30
micro_batch_size: 4
mlflow_experiment_name: /tmp/c9e5168aaf615a7c_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 10
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: c81d855a-5c46-46dc-bab6-9f15fcbfa230
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: c81d855a-5c46-46dc-bab6-9f15fcbfa230
warmup_steps: 5
weight_decay: 0.0
xformers_attention: true
db4fa482-19bd-4cd7-a722-d106a826e3e5
This model is a fine-tuned version of unsloth/Meta-Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- training_steps: 30
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0000 | 1 | nan |
| 0.0 | 0.0001 | 5 | nan |
| 0.0 | 0.0003 | 10 | nan |
| 0.0 | 0.0004 | 15 | nan |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
- Library
- peft
- Type
- llama
- License
- llama3.1
- Created
- Jan 24, 2025
- Updated
- Jan 24, 2025