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felixwangg/Qwen2.5-Coder-7B-evol-33k-stage1-insec-stage2
Qwen2.5-Coder-7B-evol-33k-stage1-insec-stage2 is a text generation model from felixwangg. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
axolotl version: 0.16.1
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
model_type: Qwen2ForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
datasets:
- path: felixwangg/prime_vul_minus_splitted
type: chat_template
split: train
test_datasets:
- path: felixwangg/prime_vul_minus_splitted
type: chat_template
split: validation
dataset_prepared_path: /u901/t577wang/SecSteer-v2/axolotl-datasets/lora/Qwen2.5-Coder-7B/evol-33k-stage1-insec-stage2
val_set_size: 0
output_dir: /u901/t577wang/SecSteer-v2/axolotl-outputs/lora/Qwen2.5-Coder-7B-evol-33k-stage1-insec-stage2
sequence_len: 4096
sample_packing: false
eval_sample_packing: false
pad_to_sequence_len: true
adapter: lora
lora_model_dir: /u901/t577wang/SecSteer-v2/axolotl-outputs/lora/Qwen2.5-Coder-7B-evol-33k-stage1/checkpoint-424
lora_r: 16
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
merge_lora: false
wandb_project: sft-primevul-sweep-ctx-0
wandb_entity: wtkuan
wandb_watch: "false"
wandb_name: Qwen2.5-Coder-7B-evol-33k-stage1-insec-stage2
wandb_log_model: "false"
gradient_accumulation_steps: 8
micro_batch_size: 4
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 4e-5
bf16: true
tf32: false
train_on_inputs: false
roles_to_train: ['assistant']
gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: true
num_epochs: 2
warmup_ratio: 0.1
early_stopping_patience: 1000
eval_steps: 15
save_steps: 15
save_total_limit: 1000
load_best_model_at_end: true
weight_decay: 0.02
special_tokens:
plugins:
</details><br>
This model is a fine-tuned version of Qwen/Qwen2.5-Coder-7B-Instruct on the felixwangg/prime_vul_minus_splitted dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Ppl | Active (gib) | Allocated (gib) | Reserved (gib) |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 0.7797 | 2.1808 | 37.83 | 37.83 | 41.81 |
| 0.7472 | 0.2655 | 15 | 0.7341 | 2.0835 | 38.14 | 38.14 | 51.31 |
| 0.7186 | 0.5310 | 30 | 0.7145 | 2.0432 | 38.14 | 38.14 | 51.31 |
| 0.6253 | 0.7965 | 45 | 0.7062 | 2.0263 | 38.14 | 38.14 | 51.31 |
| 0.7044 | 1.0531 | 60 | 0.7024 | 2.0185 | 38.14 | 38.14 | 51.31 |
| 0.7134 | 1.3186 | 75 | 0.7004 | 2.0146 | 38.14 | 38.14 | 51.31 |
| 0.6785 | 1.5841 | 90 | 0.6993 | 2.0124 | 38.14 | 38.14 | 51.31 |
| 0.6387 | 1.8496 | 105 | 0.6990 | 2.0118 | 38.14 | 38.14 | 51.31 |
| 0.6376 | 1.9912 | 113 | 0.6990 | 2.0117 | 38.14 | 38.14 | 51.31 |