---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_reciteonly_qa_v3_lora2
  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. -->

# lmind_nq_train6000_eval6489_v1_reciteonly_qa_v3_lora2

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4374
- Accuracy: 0.6510

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.168         | 1.0   | 187  | 1.1156          | 0.6787   |
| 1.0838        | 2.0   | 375  | 1.1152          | 0.6790   |
| 0.9936        | 3.0   | 562  | 1.1289          | 0.6781   |
| 0.8717        | 4.0   | 750  | 1.1731          | 0.6742   |
| 0.7555        | 5.0   | 937  | 1.2357          | 0.6711   |
| 0.6292        | 6.0   | 1125 | 1.3174          | 0.6674   |
| 0.5073        | 7.0   | 1312 | 1.4164          | 0.6638   |
| 0.4021        | 8.0   | 1500 | 1.4974          | 0.6621   |
| 0.3017        | 9.0   | 1687 | 1.6756          | 0.6576   |
| 0.2292        | 10.0  | 1875 | 1.8038          | 0.6548   |
| 0.1766        | 11.0  | 2062 | 1.9233          | 0.6539   |
| 0.1406        | 12.0  | 2250 | 2.0465          | 0.6519   |
| 0.1146        | 13.0  | 2437 | 2.1205          | 0.6518   |
| 0.0988        | 14.0  | 2625 | 2.1974          | 0.6523   |
| 0.0915        | 15.0  | 2812 | 2.2592          | 0.6519   |
| 0.0859        | 16.0  | 3000 | 2.3234          | 0.6515   |
| 0.0785        | 17.0  | 3187 | 2.3664          | 0.6515   |
| 0.0761        | 18.0  | 3375 | 2.3999          | 0.6507   |
| 0.0767        | 19.0  | 3562 | 2.4329          | 0.6517   |
| 0.0756        | 19.95 | 3740 | 2.4374          | 0.6510   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1