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
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7655 | 0.4793 | 700 | 0.9256 |
| 0.8703 | 0.9586 | 1400 | 0.9017 |
| 0.725 | 1.4379 | 2100 | 0.9006 |
| 0.7958 | 1.9172 | 2800 | 0.8908 |
| 0.7346 | 2.3964 | 3500 | 0.8911 |
| 0.6516 | 2.8757 | 4200 | 0.8911 |
| 1.0524 | 3.3550 | 4900 | 0.9006 |
| 1.1005 | 3.8343 | 5600 | 0.8945 |
| 0.7991 | 4.3136 | 6300 | 0.9009 |
| 0.7668 | 4.7929 | 7000 | 0.9016 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1
- Downloads last month
- 5
Model tree for WDong/7B_lora_06051615
Base model
Qwen/Qwen1.5-7B-Chat