---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_recite_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_lmin
  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_recite_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_lmin

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4657
- Accuracy: 0.7995

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4253        | 1.0   | 529   | 0.5042          | 0.7770   |
| 0.3444        | 2.0   | 1058  | 0.4371          | 0.7875   |
| 0.2679        | 3.0   | 1587  | 0.3925          | 0.7946   |
| 0.2195        | 4.0   | 2116  | 0.3709          | 0.7977   |
| 0.1889        | 5.0   | 2645  | 0.3616          | 0.7998   |
| 0.1724        | 6.0   | 3174  | 0.3608          | 0.8002   |
| 0.1573        | 7.0   | 3703  | 0.3646          | 0.8006   |
| 0.144         | 8.0   | 4232  | 0.3774          | 0.8000   |
| 0.1353        | 9.0   | 4761  | 0.3889          | 0.8000   |
| 0.1281        | 10.0  | 5290  | 0.3975          | 0.8000   |
| 0.124         | 11.0  | 5819  | 0.4108          | 0.7998   |
| 0.1169        | 12.0  | 6348  | 0.4183          | 0.8001   |
| 0.1128        | 13.0  | 6877  | 0.4249          | 0.7997   |
| 0.1108        | 14.0  | 7406  | 0.4259          | 0.8004   |
| 0.1078        | 15.0  | 7935  | 0.4435          | 0.7994   |
| 0.1065        | 16.0  | 8464  | 0.4421          | 0.7999   |
| 0.104         | 17.0  | 8993  | 0.4450          | 0.7998   |
| 0.103         | 18.0  | 9522  | 0.4554          | 0.7995   |
| 0.1033        | 19.0  | 10051 | 0.4556          | 0.7997   |
| 0.1041        | 20.0  | 10580 | 0.4657          | 0.7995   |


### Framework versions

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