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mta-tag-training-qwen14b-q4bit-checkpoints – AI Model by oodeh | AlphaNeural AI
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mta-tag-training-qwen14b-q4bit-checkpoints
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peft
safetensors
llama-factory
lora
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Qwen/Qwen2.5-Coder-14B-Instruct
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train_2025-02-25-10-13-47
This model is a fine-tuned version of
Qwen/Qwen2.5-Coder-14B-Instruct
on the mta dataset.
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: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 16
total_train_batch_size: 32
total_eval_batch_size: 16
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 20.0
Training results
Framework versions
PEFT 0.12.0
Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0
