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minpeter / LoRA-corrupted-bfcl-1.5B-v1
Model's Last Updated: February 21 2025
Introduction of LoRA-corrupted-bfcl-1.5B-v1
Model Details of LoRA-corrupted-bfcl-1.5B-v1
See axolotl config
axolotl version:
0.6.0
base_model: Qwen/Qwen2.5-1.5B-Instruct
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
load_in_8bit: false
load_in_4bit: false
strict: false
# datasets:
# - path: oneline-tool.jsonl
# type: chat_template
# chat_template: chatml
# field_messages: conversations
# message_field_role: from
# message_field_content: value
# - path: minpeter/stanford-alpaca-regen-llama-3.3
# type:
# format: "<|im_start|>user\n{instruction}\n{input}<|im_end|>\n<|im_start|>assistant\n"
# no_input_format: "<|im_start|>user\n{instruction}<|im_end|>\n<|im_start|>assistant\n"
# shards: 52000
datasets:
- path: minpeter/bfcl-v1-non-live-ast-hermes
data_files:
- result.parquet
type: chat_template
chat_template: chatml
field_messages: conversations
message_field_role: from
message_field_content: value
chat_template: chatml
dataset_prepared_path: last_run_prepared
output_dir: ./output
adapter: lora
lora_model_dir:
sequence_len: 2048
pad_to_sequence_len: true
sample_packing: true
# val_set_size: 0.1
# eval_sample_packing: true
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out:
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project: "axolotl"
wandb_entity: "kasfiekfs-e"
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_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
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
# special_tokens:
# bos_token: null
# eos_token: <|im_end|>
# pad_token: <|endoftext|>
output
This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the minpeter/bfcl-v1-non-live-ast-hermes dataset.
Model description
Intentionally contaminated BFCL model, 😈
🔍 Running test: parallel_multiple
✅ Test completed: parallel_multiple. 🎯 Accuracy: 0.84
🔍 Running test: parallel
✅ Test completed: parallel. 🎯 Accuracy: 0.875
🔍 Running test: simple
✅ Test completed: simple. 🎯 Accuracy: 0.94
🔍 Running test: multiple
✅ Test completed: multiple. 🎯 Accuracy: 0.89
Inference
docker run --rm --runtime nvidia --gpus '"device=0"' \
-p 8000:8000 \
-e HF_TOKEN="<secret>" \
-v ~/.cache/huggingface:/root/.cache/huggingface \
vllm/vllm-openai:latest \
--model Qwen/Qwen2.5-1.5B-Instruct \
--enable-lora \
--lora-modules \
tool=minpeter/LoRA-corrupted-bfcl-1.5B-v1 \
--enable-auto-tool-choice \
--tool-call-parser hermes
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_8BIT 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: 10
- num_epochs: 1.0
Training results
Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
Runs of minpeter LoRA-corrupted-bfcl-1.5B-v1 on huggingface.co
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More Information About LoRA-corrupted-bfcl-1.5B-v1 huggingface.co Model
Url of LoRA-corrupted-bfcl-1.5B-v1
LoRA-corrupted-bfcl-1.5B-v1 huggingface.co Url
Provider of LoRA-corrupted-bfcl-1.5B-v1 huggingface.co
Other API from minpeter
Updated:July 30 2025
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