peft tensorboard safetensors generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 region:us
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-textclassification_adalora
  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. -->

# distilbert-base-uncased-textclassification_adalora

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6697
- Precision: 0.6503
- Recall: 0.5072
- F1: 0.5699
- Accuracy: 0.9524

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 213   | 1.9179          | 0.4803    | 0.2620 | 0.3390 | 0.9371   |
| No log        | 2.0   | 426   | 1.6876          | 0.5057    | 0.3194 | 0.3915 | 0.9404   |
| 1.7592        | 3.0   | 639   | 1.4144          | 0.5161    | 0.3445 | 0.4132 | 0.9420   |
| 1.7592        | 4.0   | 852   | 1.1653          | 0.5455    | 0.3517 | 0.4276 | 0.9428   |
| 1.1731        | 5.0   | 1065  | 1.0656          | 0.575     | 0.3852 | 0.4613 | 0.9443   |
| 1.1731        | 6.0   | 1278  | 0.9946          | 0.5878    | 0.4163 | 0.4874 | 0.9461   |
| 1.1731        | 7.0   | 1491  | 0.9620          | 0.6467    | 0.4139 | 0.5047 | 0.9464   |
| 0.8895        | 8.0   | 1704  | 0.9450          | 0.6587    | 0.4294 | 0.5199 | 0.9473   |
| 0.8895        | 9.0   | 1917  | 0.9187          | 0.6382    | 0.4557 | 0.5318 | 0.9488   |
| 0.8124        | 10.0  | 2130  | 0.9042          | 0.6528    | 0.4522 | 0.5343 | 0.9493   |
| 0.8124        | 11.0  | 2343  | 0.8847          | 0.6443    | 0.4701 | 0.5436 | 0.9500   |
| 0.7741        | 12.0  | 2556  | 0.8773          | 0.6594    | 0.4677 | 0.5472 | 0.9502   |
| 0.7741        | 13.0  | 2769  | 0.8642          | 0.6672    | 0.4653 | 0.5483 | 0.9502   |
| 0.7741        | 14.0  | 2982  | 0.8439          | 0.6694    | 0.4821 | 0.5605 | 0.9514   |
| 0.7346        | 15.0  | 3195  | 0.8381          | 0.6735    | 0.4737 | 0.5562 | 0.9512   |
| 0.7346        | 16.0  | 3408  | 0.8199          | 0.6773    | 0.4844 | 0.5649 | 0.9517   |
| 0.6966        | 17.0  | 3621  | 0.8007          | 0.6744    | 0.4856 | 0.5647 | 0.9521   |
| 0.6966        | 18.0  | 3834  | 0.7845          | 0.6618    | 0.4916 | 0.5642 | 0.9520   |
| 0.6575        | 19.0  | 4047  | 0.7677          | 0.6491    | 0.5    | 0.5649 | 0.9522   |
| 0.6575        | 20.0  | 4260  | 0.7573          | 0.6624    | 0.4904 | 0.5636 | 0.9524   |
| 0.6575        | 21.0  | 4473  | 0.7419          | 0.6561    | 0.4928 | 0.5628 | 0.9522   |
| 0.6218        | 22.0  | 4686  | 0.7282          | 0.6435    | 0.4988 | 0.5620 | 0.9522   |
| 0.6218        | 23.0  | 4899  | 0.7142          | 0.6346    | 0.5048 | 0.5623 | 0.9520   |
| 0.5894        | 24.0  | 5112  | 0.7173          | 0.6474    | 0.4964 | 0.5619 | 0.9521   |
| 0.5894        | 25.0  | 5325  | 0.7132          | 0.6562    | 0.4976 | 0.5660 | 0.9526   |
| 0.5728        | 26.0  | 5538  | 0.7051          | 0.6453    | 0.5048 | 0.5664 | 0.9523   |
| 0.5728        | 27.0  | 5751  | 0.7032          | 0.6462    | 0.5024 | 0.5653 | 0.9524   |
| 0.5728        | 28.0  | 5964  | 0.6984          | 0.6405    | 0.5072 | 0.5661 | 0.9524   |
| 0.5629        | 29.0  | 6177  | 0.6973          | 0.6502    | 0.5024 | 0.5668 | 0.9523   |
| 0.5629        | 30.0  | 6390  | 0.6928          | 0.6459    | 0.5084 | 0.5689 | 0.9527   |
| 0.5543        | 31.0  | 6603  | 0.6935          | 0.6483    | 0.5072 | 0.5691 | 0.9528   |
| 0.5543        | 32.0  | 6816  | 0.6893          | 0.6448    | 0.5060 | 0.5670 | 0.9526   |
| 0.5465        | 33.0  | 7029  | 0.6893          | 0.6593    | 0.5024 | 0.5703 | 0.9524   |
| 0.5465        | 34.0  | 7242  | 0.6863          | 0.6594    | 0.5048 | 0.5718 | 0.9526   |
| 0.5465        | 35.0  | 7455  | 0.6829          | 0.6543    | 0.5072 | 0.5714 | 0.9526   |
| 0.5414        | 36.0  | 7668  | 0.6780          | 0.6464    | 0.5096 | 0.5699 | 0.9528   |
| 0.5414        | 37.0  | 7881  | 0.6776          | 0.6508    | 0.5084 | 0.5709 | 0.9526   |
| 0.5341        | 38.0  | 8094  | 0.6764          | 0.6549    | 0.5084 | 0.5724 | 0.9525   |
| 0.5341        | 39.0  | 8307  | 0.6749          | 0.6549    | 0.5084 | 0.5724 | 0.9526   |
| 0.5301        | 40.0  | 8520  | 0.6773          | 0.6640    | 0.5012 | 0.5712 | 0.9525   |
| 0.5301        | 41.0  | 8733  | 0.6730          | 0.6518    | 0.5084 | 0.5712 | 0.9525   |
| 0.5301        | 42.0  | 8946  | 0.6717          | 0.6509    | 0.5108 | 0.5724 | 0.9526   |
| 0.5268        | 43.0  | 9159  | 0.6721          | 0.6544    | 0.5096 | 0.5730 | 0.9525   |
| 0.5268        | 44.0  | 9372  | 0.6694          | 0.6480    | 0.5108 | 0.5712 | 0.9526   |
| 0.5236        | 45.0  | 9585  | 0.6709          | 0.6528    | 0.5084 | 0.5716 | 0.9525   |
| 0.5236        | 46.0  | 9798  | 0.6694          | 0.6494    | 0.5096 | 0.5710 | 0.9525   |
| 0.5231        | 47.0  | 10011 | 0.6693          | 0.6514    | 0.5096 | 0.5718 | 0.9525   |
| 0.5231        | 48.0  | 10224 | 0.6696          | 0.6503    | 0.5072 | 0.5699 | 0.9524   |
| 0.5231        | 49.0  | 10437 | 0.6699          | 0.6513    | 0.5072 | 0.5703 | 0.9524   |
| 0.5224        | 50.0  | 10650 | 0.6697          | 0.6503    | 0.5072 | 0.5699 | 0.9524   |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0