7B_lora_06051615

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06051615

This model is a fine-tuned version of Qwen/Qwen1.5-7B-Chat on the my own dataset. It achieves the following results on the evaluation set:

• Loss: 0.9018

Model description

Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. In comparison with the previous released Qwen, the improvements include:

• 8 model sizes, including 0.5B, 1.8B, 4B, 7B, 14B, 32B and 72B dense models, and an MoE model of 14B with 2.7B activated;
• Significant performance improvement in Chat models;
• Multilingual support of both base and chat models;
• Stable support of 32K context length for models of all sizes
• No need of trust_remote_code. For more details, please refer to the blog post and GitHub repo.

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: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• total_eval_batch_size: 2
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 700
• num_epochs: 5.0

Training results

Framework versions

• PEFT 0.10.0
• Transformers 4.40.0
• Pytorch 2.1.0+cu121
• Datasets 2.14.5
• Tokenizers 0.19.1