---
library_name: transformers
license: other
base_model: saves/Yi-1.5-9B-pt-241124
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: Yi-1.5-9B-sft-241128
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Yi-1.5-9B-sft-241128

This model is a fine-tuned version of [saves/Yi-1.5-9B-pt-241124](https://huggingface.co/saves/Yi-1.5-9B-pt-241124) on the chinese-medical-dialogue, the CMB, the cMedQA2, the CMExam, the CMtMedQA, the COIG-CQIA-full, the COIG_full, the HuatuoGPT_sft_data_v, the huatuo_encyclopedia_q, the huatuo_lite, the imcs21, the Med-single-choice, the Medical_dialogue_system_en_single_turn, the qizhengpt-sft-20, the self_cognition, the sharegpt_zh_38K_format, the shennong, the shibing642-medica, the tigerbot_sft_data, the xywy-KG and the zhongyi-zhiku datasets.
It achieves the following results on the evaluation set:
- Loss: 1.4478

## 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: 2.5e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.6544        | 0.1277 | 1000  | 1.6105          |
| 1.5595        | 0.2554 | 2000  | 1.5668          |
| 1.5297        | 0.3830 | 3000  | 1.5394          |
| 1.5637        | 0.5107 | 4000  | 1.5188          |
| 1.5051        | 0.6384 | 5000  | 1.5028          |
| 1.4765        | 0.7661 | 6000  | 1.4895          |
| 1.4504        | 0.8938 | 7000  | 1.4779          |
| 1.4084        | 1.0215 | 8000  | 1.4716          |
| 1.4292        | 1.1491 | 9000  | 1.4653          |
| 1.4349        | 1.2768 | 10000 | 1.4597          |
| 1.4442        | 1.4045 | 11000 | 1.4548          |
| 1.422         | 1.5322 | 12000 | 1.4517          |
| 1.3986        | 1.6599 | 13000 | 1.4491          |
| 1.3949        | 1.7875 | 14000 | 1.4482          |
| 1.4241        | 1.9152 | 15000 | 1.4478          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1