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# distilbert-base-uncased-finetuned-items-multi-label1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3682
- F1 Micro: 0.7014
- F1 Macro: 0.6332
- Hamming Loss: 0.1497
- Jaccard Score: 0.4793

## 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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Hamming Loss | Jaccard Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------------:|:-------------:|
| 0.6037        | 1.0   | 32   | 0.5429          | 0.0      | 0.0      | 0.2816       | 0.0           |
| 0.5311        | 2.0   | 64   | 0.5032          | 0.0      | 0.0      | 0.2816       | 0.0           |
| 0.466         | 3.0   | 96   | 0.4669          | 0.3740   | 0.2279   | 0.2253       | 0.1587        |
| 0.4125        | 4.0   | 128  | 0.4320          | 0.4842   | 0.3553   | 0.2019       | 0.2393        |
| 0.3546        | 5.0   | 160  | 0.4026          | 0.5436   | 0.4311   | 0.1868       | 0.2992        |
| 0.3132        | 6.0   | 192  | 0.3856          | 0.5788   | 0.4574   | 0.1799       | 0.3264        |
| 0.2733        | 7.0   | 224  | 0.3747          | 0.6469   | 0.5372   | 0.1635       | 0.4001        |
| 0.2333        | 8.0   | 256  | 0.3695          | 0.6725   | 0.5476   | 0.1552       | 0.4098        |
| 0.2046        | 9.0   | 288  | 0.3586          | 0.6818   | 0.5559   | 0.1538       | 0.4161        |
| 0.1819        | 10.0  | 320  | 0.3578          | 0.6949   | 0.6108   | 0.1484       | 0.4566        |
| 0.1624        | 11.0  | 352  | 0.3649          | 0.6742   | 0.5884   | 0.1593       | 0.4345        |
| 0.1457        | 12.0  | 384  | 0.3565          | 0.6870   | 0.6134   | 0.1552       | 0.4593        |
| 0.1288        | 13.0  | 416  | 0.3592          | 0.6961   | 0.6263   | 0.1511       | 0.4733        |
| 0.1193        | 14.0  | 448  | 0.3682          | 0.6852   | 0.6097   | 0.1552       | 0.4577        |
| 0.1113        | 15.0  | 480  | 0.3643          | 0.6947   | 0.6215   | 0.1497       | 0.4704        |
| 0.1023        | 16.0  | 512  | 0.3652          | 0.6959   | 0.6265   | 0.1525       | 0.4740        |
| 0.0942        | 17.0  | 544  | 0.3730          | 0.6925   | 0.6262   | 0.1525       | 0.4726        |
| 0.0906        | 18.0  | 576  | 0.3687          | 0.7014   | 0.6372   | 0.1497       | 0.4825        |
| 0.0893        | 19.0  | 608  | 0.3657          | 0.7033   | 0.6317   | 0.1484       | 0.4797        |
| 0.0882        | 20.0  | 640  | 0.3682          | 0.7014   | 0.6332   | 0.1497       | 0.4793        |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-items-multi-label1", "results": []}]}
transformers tensorboard safetensors distilbert text-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us