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--- |
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license: mit |
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library_name: peft |
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tags: |
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- llama-factory |
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- lora |
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- generated_from_trainer |
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base_model: Qwen/Qwen1.5-7B-Chat |
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model-index: |
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- name: '06051615' |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# 06051615 |
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This model is a fine-tuned version of [Qwen/Qwen1.5-7B-Chat](https://huggingface.co/Qwen/Qwen1.5-7B-Chat) on the my own dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9018 |
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## Model description |
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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: |
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* 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; |
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* Significant performance improvement in Chat models; |
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* Multilingual support of both base and chat models; |
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* Stable support of 32K context length for models of all sizes |
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* No need of `trust_remote_code`. |
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For more details, please refer to the [blog post](https://qwenlm.github.io/blog/qwen1.5/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5). |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 2 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 700 |
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- num_epochs: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.7655 | 0.4793 | 700 | 0.9256 | |
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| 0.8703 | 0.9586 | 1400 | 0.9017 | |
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| 0.725 | 1.4379 | 2100 | 0.9006 | |
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| 0.7958 | 1.9172 | 2800 | 0.8908 | |
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| 0.7346 | 2.3964 | 3500 | 0.8911 | |
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| 0.6516 | 2.8757 | 4200 | 0.8911 | |
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| 1.0524 | 3.3550 | 4900 | 0.9006 | |
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| 1.1005 | 3.8343 | 5600 | 0.8945 | |
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| 0.7991 | 4.3136 | 6300 | 0.9009 | |
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| 0.7668 | 4.7929 | 7000 | 0.9016 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.19.1 |
