File size: 1,572 Bytes
0681559 d5f0295 0681559 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
---
librar_yname: transformers
license: other
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- llama-factory
- freeze
- generated_from_trainer
model-index:
- name: output
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# output
This model is a fine-tuned version of Qwen2.5-1.5B-Instruct on the alpaca_zh_demo dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9959
## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0102 | 1.1111 | 500 | 1.7723 |
| 0.5375 | 2.2222 | 1000 | 1.9768 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.3.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.3
|