|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: mistralai/Mistral-7B-Instruct-v0.3 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: mistral-7b-instruct-v0.3-mimic4-adapt-l2r |
|
|
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. --> |
|
|
|
|
|
# mistral-7b-instruct-v0.3-mimic4-adapt-l2r |
|
|
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: -443630515076000256.0000 |
|
|
- Ndcg: 0.9572 |
|
|
- Ndcg@25: 0.8320 |
|
|
- Precision@25: 0.9131 |
|
|
|
|
|
## 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: 4 |
|
|
- total_train_batch_size: 4 |
|
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 5 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Ndcg | Ndcg@25 | Precision@25 | |
|
|
|:-------------------------:|:------:|:----:|:------------------------:|:------:|:-------:|:------------:| |
|
|
| -820244910218569344.0000 | 1.0 | 44 | -138641363343365152.0000 | 0.9556 | 0.1965 | 0.0 | |
|
|
| -92176210412856928.0000 | 2.0 | 88 | -325691602546540992.0000 | 0.9565 | 0.6500 | 0.5451 | |
|
|
| -1386633586255750656.0000 | 3.0 | 132 | -437409861527509376.0000 | 0.9569 | 0.7879 | 0.9086 | |
|
|
| -352078631547594368.0000 | 4.0 | 176 | -441613587243874944.0000 | 0.9572 | 0.8426 | 0.9143 | |
|
|
| -4554006957848212480.0000 | 4.9017 | 215 | -443630515076000256.0000 | 0.9572 | 0.8320 | 0.9131 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.49.0 |
|
|
- Pytorch 2.6.0 |
|
|
- Datasets 3.6.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
