---
library_name: transformers
base_model: cam-1000/MNLP_M3_mcqa_model
tags:
- generated_from_trainer
model-index:
- name: MNLP_M3_rag_model
  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. -->

# MNLP_M3_rag_model

This model is a fine-tuned version of [cam-1000/MNLP_M3_mcqa_model](https://huggingface.co/cam-1000/MNLP_M3_mcqa_model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8564

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.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: 0.01
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8275        | 0.0228 | 100  | 0.8105          |
| 0.7663        | 0.0456 | 200  | 0.8251          |
| 0.5896        | 0.0683 | 300  | 0.8564          |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.7.0+cu126
- Datasets 3.2.0
- Tokenizers 0.21.0