---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_reciteonly_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_
  results: []
library_name: peft
---

<!-- 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__home_aiops_zhuty_lm_indexer_data_tyzhu_

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0955
- Accuracy: 0.7196

## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.7054        | 0.9973  | 187  | 0.5535          | 0.7686   |
| 0.4975        | 2.0     | 375  | 0.5416          | 0.7693   |
| 0.422         | 2.9973  | 562  | 0.5611          | 0.7645   |
| 0.3527        | 4.0     | 750  | 0.6100          | 0.7573   |
| 0.2941        | 4.9973  | 937  | 0.6599          | 0.7522   |
| 0.2518        | 6.0     | 1125 | 0.7200          | 0.7458   |
| 0.2138        | 6.9973  | 1312 | 0.7651          | 0.7421   |
| 0.1824        | 8.0     | 1500 | 0.8280          | 0.7379   |
| 0.1481        | 8.9973  | 1687 | 0.8700          | 0.7355   |
| 0.1298        | 10.0    | 1875 | 0.9146          | 0.7329   |
| 0.1167        | 10.9973 | 2062 | 0.9337          | 0.7309   |
| 0.1094        | 12.0    | 2250 | 0.9733          | 0.7281   |
| 0.1052        | 12.9973 | 2437 | 0.9980          | 0.7266   |
| 0.1007        | 14.0    | 2625 | 1.0022          | 0.7256   |
| 0.0971        | 14.9973 | 2812 | 1.0422          | 0.7234   |
| 0.0954        | 16.0    | 3000 | 1.0441          | 0.7236   |
| 0.0888        | 16.9973 | 3187 | 1.0574          | 0.7223   |
| 0.0879        | 18.0    | 3375 | 1.0728          | 0.7216   |
| 0.0879        | 18.9973 | 3562 | 1.0768          | 0.7200   |
| 0.0883        | 19.9467 | 3740 | 1.0955          | 0.7196   |


### Framework versions

- PEFT 0.5.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1