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---
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
|