train_2025-02-25-10-13-47
This model is a fine-tuned version of Qwen/Qwen2.5-Coder-14B-Instruct on the clc-ui-e2e 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: 8
- total_train_batch_size: 16
- 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
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Model tree for oodeh/clc-ui-e2e-tag-training-qwen14b-q4bit-checkpoints
Base model
Qwen/Qwen2.5-14B
Finetuned
Qwen/Qwen2.5-Coder-14B
Finetuned
Qwen/Qwen2.5-Coder-14B-Instruct