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Bepemin / 6963ac37-504f-4ca0-a67b-13fed2c733eb
Model's Last Updated: January 30 2025
Introduction of 6963ac37-504f-4ca0-a67b-13fed2c733eb
Model Details of 6963ac37-504f-4ca0-a67b-13fed2c733eb
See axolotl config
axolotl version:
0.4.1
adapter: lora
base_model: microsoft/Phi-3.5-mini-instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 1105cd39b022986f_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/1105cd39b022986f_train_data.json
type:
field_instruction: input
field_output: output_answer
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 1
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: nghiatrannnnnn/6963ac37-504f-4ca0-a67b-13fed2c733eb
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: true
load_in_8bit: true
local_rank: null
logging_steps: 1
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: 200
micro_batch_size: 2
mlflow_experiment_name: /tmp/1105cd39b022986f_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
saves_per_epoch: 1
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 18ebd1fa-1456-4c4e-a37b-e85673769722
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 18ebd1fa-1456-4c4e-a37b-e85673769722
warmup_steps: 5
weight_decay: 0.01
xformers_attention: true
6963ac37-504f-4ca0-a67b-13fed2c733eb
This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8255
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 200
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.785 | 0.0145 | 200 | 0.8255 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
Runs of Bepemin 6963ac37-504f-4ca0-a67b-13fed2c733eb on huggingface.co
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More Information About 6963ac37-504f-4ca0-a67b-13fed2c733eb huggingface.co Model
Url of 6963ac37-504f-4ca0-a67b-13fed2c733eb
6963ac37-504f-4ca0-a67b-13fed2c733eb huggingface.co Url
Provider of 6963ac37-504f-4ca0-a67b-13fed2c733eb huggingface.co
Other API from Bepemin
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